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	<title>DevOps Archives - CDInsights</title>
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	<title>DevOps Archives - CDInsights</title>
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		<title>3 DevOps Strategies for Cloud Automation and Integration</title>
		<link>https://www.clouddatainsights.com/3-devops-strategies-for-cloud-automation-and-integration/</link>
					<comments>https://www.clouddatainsights.com/3-devops-strategies-for-cloud-automation-and-integration/#respond</comments>
		
		<dc:creator><![CDATA[Venkat Thiruvengadam]]></dc:creator>
		<pubDate>Sat, 20 Jul 2024 13:06:19 +0000</pubDate>
				<category><![CDATA[Cloud Data Platforms]]></category>
		<category><![CDATA[cloud automation]]></category>
		<category><![CDATA[DevOps]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=5287</guid>

					<description><![CDATA[Discover three approaches to DevOps for mastering automation and integration in the cloud era.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full"><img fetchpriority="high" decoding="async" width="999" height="545" src="https://www.clouddatainsights.com/wp-content/uploads/2024/07/Depositphotos_378696164_S.jpg" alt="devops automation and integration" class="wp-image-5288" srcset="https://www.clouddatainsights.com/wp-content/uploads/2024/07/Depositphotos_378696164_S.jpg 999w, https://www.clouddatainsights.com/wp-content/uploads/2024/07/Depositphotos_378696164_S-300x164.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2024/07/Depositphotos_378696164_S-768x419.jpg 768w" sizes="(max-width: 999px) 100vw, 999px" /><figcaption class="wp-element-caption"><em>Discover three approaches to DevOps for mastering automation and integration in the cloud era.</em></figcaption></figure></div>


<p>The terrain of DevOps is ever-changing, marked by an ecosystem rich with a variety of software applications catering to diverse functionalities across the cloud infrastructure landscape. Today, the tide is turning towards a holistic view of DevOps Automation, with the industry shifting its focus to comprehensive, end-to-end platform-based solutions.</p>



<p>Organizations are discovering a spectrum of possibilities in cloud engagement. Some dip their toes with a select few containerized applications, leveraging essential data storage solutions such as SQL servers and S3 object stores. In contrast, others dive deep into the pool of services exclusive to cloud providers like AWS&#8217;s arsenal, which includes SQS, SNS, Dynamo, Lambda, EMR, RDS, MSK, and the list goes on. As for compliance, while many are content with basic best practices, some are navigating the strict channels of SOC2, HIPAA, PCI, and NIST standards.</p>



<p>See also: <a href="https://www.clouddatainsights.com/the-technology-behind-and-benefits-of-data-pipeline-automation/">The Technology Behind and Benefits of Data Pipeline Automation</a></p>



<p>Imagine a fully cloud-native application infrastructure within AWS. This same scenario, with variations unique to their ecosystems, is mirrored across Azure and GCP—each providing a unique set of proprietary services.</p>



<p>In this evolving narrative, three DevOps Automation approaches stand out:</p>



<ol class="wp-block-list">
<li>The Do-It-Yourself Route with Infrastructure-as-Code</li>



<li>Platform-as-a-Service (PaaS) Abstraction</li>



<li>Platform Engineering Innovation</li>
</ol>



<figure class="wp-block-image"><img decoding="async" src="https://lh7-us.googleusercontent.com/docsz/AD_4nXdX8N_pv5yxsYB6BTjKUb-D7VQyjF7AM1CPZjeSUmOUXwsAxpu4xvOlZNJAMrCSDbQ92AcgOAkCxiW0vbhdkqBw7XO0tZBRABjeQP8Iip7z29gS03fSUCdhGxJklolu4i5K3oGDbX80W3kEi-PfQPVVv7eHVHqDn6w5t36x1PI7-dXeJblKPwY?key=x8fDxIzhDsbiI-fnhqQY_Q" alt=""/></figure>



<h3 class="wp-block-heading">1. Crafting Your Path with Infrastructure-as-Code</h3>



<p>The classic method involves a hands-on approach, where teams intricately script using tools like Terraform and Pulumi. Here, a dedicated force of DevOps engineers stitches together a tapestry of solutions—managing everything from Kubernetes orchestration to access policies and audit trails. This route prizes the developer&#8217;s skill to update application code through CI/CD pipelines.</p>



<p>However, while customization and flexibility are hallmarks here, high operational costs and the risk of human error remain substantial drawbacks. The rigidity of this approach can often curtail developer autonomy, stymieing agility and response times.</p>



<h3 class="wp-block-heading">2. The PaaS Perspective</h3>



<p>PaaS solutions like Heroku and Aptible add a thick abstraction layer atop AWS, Azure, and GCP. These platforms convert cloud providers into a utility for raw compute, storage, and networking. With PaaS, teams can access a ready-made orchestration for Kubernetes, CI/CD, and Observability, along with a bespoke selection of standard applications.</p>



<p>Distinct PaaS variants exist: one operates within the user&#8217;s cloud account, while the other, like Heroku, is hosted independently, distancing the organization from direct cloud account interaction. PaaS offers a streamlined start for simple applications and a degree of developer self-service within its supported services. However, it often leaves a significant portion of DevOps operations and security management outside its jurisdiction, presenting a challenge for compliance and leading to higher costs.</p>



<h3 class="wp-block-heading">3. The Rise of Platform Engineering</h3>



<p>The latest in the DevOps saga is the surge of Platform Engineering or Internal Developer Platforms (IDP), which aim to gift developers with the tools to manage their cloud infrastructure end-to-end. It&#8217;s a revolution still in its youth, not quite a staple in the software categories.</p>



<h3 class="wp-block-heading">Building In-House</h3>



<p>When crafting an IDP from scratch, teams often find themselves retracing the Do-It-Yourself steps, albeit with a narrow set of self-service options. They might employ platforms like Backstage.io to erect developer portals, offering standardized templates for deployment. Despite these efforts, the static nature of templates struggles against the dynamic backdrop of the cloud, leaving developers still dependent on DevOps for nuanced changes.</p>



<h3 class="wp-block-heading">Choosing a Ready-Made Solution</h3>



<p>On the other hand, purchasing a platform engineering solution introduces a new breed of efficiency. Seasoned DevOps tool vendors are expanding their offerings to include IDPs, as seen with Harness.io and GitLab. There are also niche solutions on the market that cover a broader array of cloud-native functions.</p>



<p>Some offer a more robust solution for CD, provisioning, and security compared to Harness and GitLab&#8217;s CI-focused offerings. </p>



<p>The DevOps automation narrative is in flux, with companies seeking a balance between tailor-made solutions and user-friendly platforms, cost effectiveness, and compliance adherence. The horizons of DevOps automation are broadening towards solutions that not only simplify cloud operations but also sync harmoniously with the strategic imperatives and real-world demands of modern enterprises. As we witness the maturation of this field, we anticipate a suite of integrated solutions designed to navigate the intricate web of cloud operations.</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img alt='Venkat Thiruvengadam' src='https://secure.gravatar.com/avatar/5dea9cda9154bcc0a89fc7c932ecec04?s=100&#038;d=mm&#038;r=g' srcset='https://secure.gravatar.com/avatar/5dea9cda9154bcc0a89fc7c932ecec04?s=200&#038;d=mm&#038;r=g 2x' class='avatar avatar-100 photo' height='100' width='100' itemprop="image"/></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/venkat-thiruvengadam/" class="vcard author" rel="author"><span class="fn">Venkat Thiruvengadam</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>Venkat Thiruvengadam is the Founder and CEO of <strong><a href="https://duplocloud.com/">DuploCloud</a></strong>.</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">5287</post-id>	</item>
		<item>
		<title>How to Eradicate Technical Debt in the Cloud: Lessons from DevOps</title>
		<link>https://www.clouddatainsights.com/how-to-eradicate-technical-debt-in-the-cloud-lessons-from-devops/</link>
					<comments>https://www.clouddatainsights.com/how-to-eradicate-technical-debt-in-the-cloud-lessons-from-devops/#respond</comments>
		
		<dc:creator><![CDATA[Elizabeth Wallace]]></dc:creator>
		<pubDate>Thu, 01 Jun 2023 22:51:30 +0000</pubDate>
				<category><![CDATA[Cloud Strategy]]></category>
		<category><![CDATA[cloud computing]]></category>
		<category><![CDATA[data engineering]]></category>
		<category><![CDATA[DevOps]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=2917</guid>

					<description><![CDATA[The DevOps software development workflow can be adapted to cloud development to reduce technical debt in the cloud. Read on to discover how.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2023/05/Depositphotos_333486188_S.jpg" alt="" class="wp-image-2918" width="750" height="500" srcset="https://www.clouddatainsights.com/wp-content/uploads/2023/05/Depositphotos_333486188_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2023/05/Depositphotos_333486188_S-300x200.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2023/05/Depositphotos_333486188_S-768x512.jpg 768w, https://www.clouddatainsights.com/wp-content/uploads/2023/05/Depositphotos_333486188_S-930x620.jpg 930w" sizes="(max-width: 750px) 100vw, 750px" /><figcaption class="wp-element-caption"><em>The DevOps software development workflow</em>.</figcaption></figure></div>


<p>Technical debt isn&#8217;t just an inconvenience on the way to getting data insights. It can have profound consequences for companies seeking digital transformation and survival post-pandemic. The public is less forgiving than ever of company missteps, and if they turn out to be unavoidable, companies may suffer from the consequences of technical debt for years.</p>



<p>See also: <a href="https://www.clouddatainsights.com/what-is-mlops-elements-of-a-basic-mlops-workflow/">What is MLOps? The Elements of a Basic MLOps Workflow</a></p>



<p>And while companies definitely don&#8217;t want to replicate the same problems they have in current technology stacks when moving to the cloud, cloud environments do offer a way to minimize technical debt with the right strategies. Fortunately, DevOps techniques provide a powerful set of tools and practices that can be used to reduce technical debt in cloud-based data science environments. In this article, we&#8217;ll look at three DevOps techniques that can be used to manage technical debt, as well as their practical applications in cloud-based data science environments.</p>



<h3 class="wp-block-heading">Understanding Technical Debt in Cloud-Based Data Science Environments</h3>



<p>Technical debt happens when developers take shortcuts in the development process, leading to decreased code quality and increased maintenance requirements over time. Each developer solves an immediate challenge through one of these shortcuts, making it more difficult for future developers to understand what&#8217;s happening the next time something goes wrong. In cloud-based data science environments, technical debt can be particularly challenging to manage due to the complexity and scalability of these environments.</p>



<p>Technical debt can manifest itself in a variety of ways in cloud-based data science environments. For instance, manual infrastructure provisioning can lead to inconsistencies and increased maintenance requirements over time. Additionally, ad hoc code changes can lead to version control issues and reduced code quality.</p>



<p>Furthermore, data scientists may face different challenges in managing technical debt due to the rapidly evolving nature of cloud-based data science environments. As cloud infrastructure and services continue to evolve, new technical debt may arise, requiring data scientists to remain vigilant in managing technical debt.</p>



<p><strong>See also:</strong> <a href="https://www.clouddatainsights.com/data-pipeline-pitfalls-unraveling-the-technical-debt-tangle/" target="_blank" rel="noreferrer noopener">Data Pipeline Pitfalls: Unraveling the Technical Debt Tangle</a></p>



<h3 class="wp-block-heading">Leveraging DevOps techniques to avoid replicating technical debt in the cloud</h3>



<p>Principle DevOps techniques can help companies and engineering teams reduce the chances of replicating technical debt when adopting cloud computing. Here are three pillars of DevOps</p>



<h4 class="wp-block-heading">Continuous Integration (CI)</h4>



<p>Continuous Integration (CI) is a DevOps technique sees developers regularly integrating code changes into a shared repository instead of working in a silo. This technique can help data scientists manage technical debt by identifying code integration issues early in the development process, reducing the risk of introducing technical debt into production environments.</p>



<p>To implement CI in cloud-based data science environments, data scientists can leverage continuous integration tools explicitly designed with CI principles in mind. These tools provide a range of features such as automated testing, code reviews, and integration with source control systems like Git, helping data scientists identify code integration issues before they impact production environments.</p>



<h4 class="wp-block-heading">Continuous Delivery (CD)</h4>



<p>Continuous Delivery (CD) is a DevOps technique that involves automating the deployment of code changes to production environments. CD can help data scientists manage technical debt by reducing the risk of human error during manual deployment processes.</p>



<p>To implement CD in cloud-based data science environments, data scientists can leverage tools such as Kubernetes or Docker. These tools provide a range of features, such as automated deployment, blue-green deployments, and automatic scaling, helping data scientists reduce technical debt associated with manual deployment processes.</p>



<h4 class="wp-block-heading">Infrastructure as Code (IaC)</h4>



<p>Infrastructure as Code (IaC) is a DevOps technique that involves automating infrastructure provisioning using code. IaC can help data scientists manage technical debt by reducing the risk of inconsistencies associated with manual infrastructure provisioning processes.</p>



<p>To implement IaC in cloud-based data science environments, data scientists can leverage tools that provide a range of features such as infrastructure automation, version control, and infrastructure testing. These help data scientists and engineering teams reduce technical debt associated with manual infrastructure provisioning processes.</p>



<h3 class="wp-block-heading">Practical Applications of DevOps Techniques in Cloud-Based Data Science Environments</h3>



<p>Let&#8217;s illustrate the practical applications of DevOps techniques in cloud-based data science environments through two common scenarios: infrastructure provisioning and code deployment.</p>



<h4 class="wp-block-heading">Infrastructure Provisioning</h4>



<p>In cloud-based data science environments, infrastructure provisioning can be a significant source of technical debt due to the complexity of these environments. To reduce technical debt associated with manual infrastructure provisioning, data scientists can implement IaC techniques using designated tools.</p>



<p>For instance, data scientists can define their infrastructure using code and store it in a version control system such as Git. They can then use a different tool such as Terraform to automatically provision infrastructure based on this code definition, reducing the risk of inconsistencies and increasing the repeatability of infrastructure provisioning processes.</p>



<p>Moreover, IaC tools can be used to test and validate infrastructure changes before they are deployed, reducing the risk of introducing technical debt into production environments. For example, data scientists can use Terraform&#8217;s plan functionality to preview changes before applying them, allowing them to catch errors and issues early in the development process.</p>



<h4 class="wp-block-heading">Code Deployment</h4>



<p>Code deployment can also be a significant source of technical debt in cloud-based data science environments. To reduce technical debt associated with manual code deployment processes, data scientists can implement CD techniques using tools like Kubernetes, Docker, or AWS Elastic Beanstalk.</p>



<p>For example, data scientists can use Kubernetes to automate deploying, scaling, and managing containerized applications. Kubernetes can be used to define deployment strategies, such as blue-green deployments, that reduce the risk of downtime and enable rollbacks in case of issues. Additionally, Kubernetes can automatically scale applications based on usage metrics, reducing the risk of performance issues and increasing the reliability of applications.</p>



<p>AWS Elastic Beanstalk is another tool that can be used to automate code deployment in cloud-based data science environments. Elastic Beanstalk can automatically provision and manage the underlying infrastructure required to run applications, allowing data scientists to focus on developing code. Elastic Beanstalk supports a range of programming languages and frameworks, making it a flexible option for data scientists.</p>



<h3 class="wp-block-heading">Unraveling technical debt in cloud environments</h3>



<p>Managing technical debt in cloud-based data science environments is a significant challenge. Still, DevOps techniques offer a powerful set of tools and practices that can be used to reduce technical debt and improve productivity. Data scientists can automate infrastructure provisioning and code deployment, reducing the risk of inconsistencies and human error. Additionally, these techniques can provide greater visibility and control over infrastructure and code changes, allowing data scientists to manage technical debt more effectively.</p>



<p>Companies should consider implementing DevOps techniques to reduce technical debt in their cloud-based data science environments. These techniques can help data scientists manage technical debt, reduce the risk of introducing technical debt into production environments, and improve the reliability and scalability of data science applications.</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/Elizabeth-Wallace-RTInsights-141x150-1.jpg" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/elizabeth-wallace/" class="vcard author" rel="author"><span class="fn">Elizabeth Wallace</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>Elizabeth Wallace is a Nashville-based freelance writer with a soft spot for data science and AI and a background in linguistics. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain &#8211; clearly &#8211; what it is they do.</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">2917</post-id>	</item>
		<item>
		<title>Uber Deploys Exactly-Once Processing System for Ads</title>
		<link>https://www.clouddatainsights.com/uber-deploys-exactly-once-processing-system-for-ads/</link>
					<comments>https://www.clouddatainsights.com/uber-deploys-exactly-once-processing-system-for-ads/#respond</comments>
		
		<dc:creator><![CDATA[David Curry]]></dc:creator>
		<pubDate>Wed, 16 Nov 2022 14:23:46 +0000</pubDate>
				<category><![CDATA[AI/ML]]></category>
		<category><![CDATA[Apache Kafka]]></category>
		<category><![CDATA[DevOps]]></category>
		<category><![CDATA[Practitioner]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=2023</guid>

					<description><![CDATA[Uber's new ad processing system was built with open-source technologies and an innovative exactly-once semantic system for accuracy and reliability.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/11/uber-2-Depositphotos_164444528_S.jpg" alt="" class="wp-image-2024" width="748" height="482" srcset="https://www.clouddatainsights.com/wp-content/uploads/2022/11/uber-2-Depositphotos_164444528_S.jpg 997w, https://www.clouddatainsights.com/wp-content/uploads/2022/11/uber-2-Depositphotos_164444528_S-300x193.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2022/11/uber-2-Depositphotos_164444528_S-768x495.jpg 768w" sizes="(max-width: 748px) 100vw, 748px" /><figcaption class="wp-element-caption"><em>Uber&#8217;s new ad processing system was built with open-source technologies and an innovative exactly-once semantic system for accuracy and reliability.</em></figcaption></figure></div>


<p>Uber recently launched a new ad system for vendors on Uber Eats, allowing them to purchase sponsored space on the app, alongside other inventory.&nbsp;</p>



<p>The <a href="https://www.uber.com/en-GB/blog/real-time-exactly-once-ad-event-processing/" target="_blank" rel="noreferrer noopener">ad system</a> was a “greenfield” project, as Uber had not built ads into its mobility or freight service. That provided the team with the freedom to build a system from the ground-up, which could comprehensively meet client needs.&nbsp;</p>



<p><strong>See also:</strong> <a href="https://www.clouddatainsights.com/unifying-the-data-warehouse-and-data-lake-creates-a-new-analytical-rhythm/" target="_blank" rel="noreferrer noopener">Unifying the Data Warehouse and Data Lake Creates a New Analytical Rhythm</a></p>



<p>“This system is responsible for processing all the events that get generated from ads,” <a href="https://home.mlops.community/public/videos/real-time-model-inference-in-a-video-streaming-environment-2022-05-05">said</a> Jacob Tsafatinos, ex-senior software engineer at Uber and lead engineer of the project, in an online presentation. “It has a lot of dependencies, the clients for this system are data scientists, engineers, operations managers for vendors, automated systems, and advertisers. When we talk about the amount of requirements, they come from trying to balance the different needs of each client.”</p>



<p>The three key requirements of the processing system were:&nbsp;</p>



<ul class="nv-cv-m wp-block-list">
<li>Speed: Having a near-real time system provides clients with a clearer understanding of how much ad budget has been spent. For example, a vendor can reduce the amount of impressions or stall the ad campaign for a set time if there’s been too many sales in a single day.&nbsp;</li>



<li>Reliability: Anything money related needs to be reliable in order to gain client trust. Uber very rarely goes down, and its backend has been built in a similar way to let clients always have access to their dashboard.&nbsp;</li>



<li>Accuracy: As with reliability, a processing system dealing with money needs to be accurate. If Uber were to overcharge a client, it could lead to them stopping their ad campaign, if they undercharge it costs the company.&nbsp;</li>
</ul>



<p>One of the main functionalities of the ad processing system is exactly-once semantics for delivery, which helps Uber deal with some of the reliability and accuracy problems inherent in a processing system.&nbsp;</p>



<p>“Exactly-once was crucial for the reliability and the accuracy,” said Tsafatinos. “Flink jobs go down for a variety of reasons, and this entire project is built off the back of Flink. When an issue happens, it restarts and reprocesses all the events from the last time it saved, and if you reprocess ad events you&#8217;re going to end up overcharging clients. It really helps with the accuracy guarantees that you need, and when things go wrong you do have that confidence to know we&#8217;re not going to reprocess everything.”</p>



<p>The choice of Apache Flink, Kafka, and Pinot were made for several reasons. Uber is one of the biggest deployers of Kafka in the world, so it was clear the framework would be used for message queues. Flink and Pinot offered key advantages for client value, ease-of-development, and the needs of the system.&nbsp;</p>



<p>Speaking on Uber’s decision to work on open-source, Tsafatinos said: &#8220;I think it says a lot about the state of open-source because these tools can be leveraged by massive companies but they&#8217;re the kinds of companies that give back to the scene.&#8221;</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/curry-150x150-1.webp" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/david-curry/" class="vcard author" rel="author"><span class="fn">David Curry</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><div class="author-info">
<div class="author-description">
<p>David is a technology writer with several years experience covering all aspects of IoT, from technology to networks to security.</p>
</div>
</div>
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		<post-id xmlns="com-wordpress:feed-additions:1">2023</post-id>	</item>
		<item>
		<title>Cloud Basics: Environment-as-a-Service</title>
		<link>https://www.clouddatainsights.com/cloud-basics-environment-as-a-service/</link>
					<comments>https://www.clouddatainsights.com/cloud-basics-environment-as-a-service/#respond</comments>
		
		<dc:creator><![CDATA[Elizabeth Wallace]]></dc:creator>
		<pubDate>Fri, 04 Nov 2022 14:36:44 +0000</pubDate>
				<category><![CDATA[Cloud Data Platforms]]></category>
		<category><![CDATA[Cloud Strategy]]></category>
		<category><![CDATA[DevOps]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=1980</guid>

					<description><![CDATA[Environment-as-a-Service offers companies the chance to improve the development lifecycle in the cloud. Here's what's most important. ]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/11/Depositphotos_254024538_S.jpg" alt="" class="wp-image-1981" width="750" height="500" srcset="https://www.clouddatainsights.com/wp-content/uploads/2022/11/Depositphotos_254024538_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2022/11/Depositphotos_254024538_S-300x200.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2022/11/Depositphotos_254024538_S-768x512.jpg 768w, https://www.clouddatainsights.com/wp-content/uploads/2022/11/Depositphotos_254024538_S-930x620.jpg 930w" sizes="(max-width: 750px) 100vw, 750px" /><figcaption class="wp-element-caption">Developers can improve quality and time to market with Environment-as-a-Service.</figcaption></figure></div>


<p>Everything-as-a-Service (XaaS) offers companies the chance to leverage the best of cloud operations—flexibility, scalability, and improved speed. They&#8217;re incredibly useful in what&#8217;s quickly becoming a cloud-dominant world, and with each new iteration, companies have more tools at the ready to improve operations and deliver dynamic customer experiences.</p>



<p>Environment-as-a-Service (EaaS) can be a game-changer for businesses eager to deploy the best in new tech but short on either time or experts able to manage rapid tech deployments. Let&#8217;s explore what EaaS can offer.</p>



<h3 class="wp-block-heading">Environment-as-a-Service grew from Infrastructure-as-a-Service</h3>



<p>Infrastructure-as-a-Service provides companies with storage, networking, and computing resources on demand. It&#8217;s associated with virtual machines that require customization as company needs change and technology deployments evolve. Thanks to complex workflows, companies may need more context to continue those deployments.</p>



<p>Environment-as-a-Service is an offshoot, offering both the application and the environment. Basically, EaaS provides the code and settings in addition to hardware and base software. IT teams can run applications in an isolated environment by describing it to the larger system and allowing the EaaS platform to do all the heavy lifting.</p>



<h3 class="wp-block-heading">Reasons companies may want to use EaaS</h3>



<p>There are three significant benefits to adopting EaaS, each of which can have huge impacts on both day-to-day operations and future projections.</p>



<h4 class="wp-block-heading">Controlling spiraling cloud costs</h4>



<p>Companies moved quickly to the cloud for the promise of improving flexibility and reaction time. However, the cloud can sometimes obscure <a href="https://www.clouddatainsights.com/youve-migrated-to-the-cloud-now-what-4-critical-cost-saving-practices/">how much it costs</a> to run processing tasks, and more companies are discovering how easy it is to run over budget accidentally.</p>



<p>EaaS can help companies control costs by first reducing the time teams spend manually setting up new environments. It reuses program elements, allowing companies to iterate more quickly during the development lifecycle. In addition, because environments are repeatable, maintenance costs are reduced.</p>



<p>EaaS also helps companies better estimate how much future environments will cost to deploy and maintain. They can limit the number to reduce complexity, and that streamlining helps prevent unexpected costs from surprising companies.</p>



<h4 class="wp-block-heading">Faster innovation and development</h4>



<p>It isn&#8217;t that development couldn&#8217;t speed up in the past. Companies needed a way to speed up the development lifecycle without sacrificing quality. Rushed jobs result in poor performance, misplaced customer expectations, and the loss of brand reputation as companies scramble to fix what&#8217;s broken.</p>



<p>Teams can create new staging environments quickly by reusing old components and eliminating testing bottlenecks. The platform can react in real time to the activity of development teams while minimizing underutilized tools. Teams can test earlier on and smooth out defects before each release.</p>



<h4 class="wp-block-heading">Greater flexibility with less waste</h4>



<p>Teams can develop and launch as many environments as they need and simply shut down what they don&#8217;t end up using. This allows companies to work faster and smarter, often concurrently, without waiting for the infrastructure to follow. In addition, EaaS reduces the tools and environments teams don&#8217;t need or haven&#8217;t used for a while.</p>



<p>This option controls the growing complexity within the cloud. Right now, companies are in danger of launching applications and losing track of what their teams are using. This way, organizations can follow a leaner development cycle that adapts as needed.</p>



<h4 class="wp-block-heading">EaaS use cases</h4>



<p>In the past, environments created for non-production tasks were costly and time-consuming. This created a bottleneck in the development lifecycle, with teams waiting for their chance to test new applications before deployment. In some cases, teams adopted shadow IT to help speed up development and reach goals, putting the organization at a disadvantage for governance and security. Solving this challenge provides some of the most compelling use cases for EaaS.</p>



<ul class="nv-cv-d nv-cv-m wp-block-list">
<li>Staging environments: These are replicas of production environments, so teams must be able to duplicate them easily with all necessary code, specifications, and data. EaaS allows for fast production of these isolated environments and simple shut-downs when not in use.</li>



<li>Test and QA environments: Similar to staging, test environments also need fast setup. The challenge here is speed and quantity. EaaS allows teams to build as many as necessary and work concurrently with other team members to reach the next development stage confidently.</li>



<li>Migrations: EaaS provides companies with an easy-to-scale environment to test migrations, including all necessary code and environment conditions. Companies can measure the impact of migrations before ever pushing to deployment.</li>



<li>Sales demos: Customers often want to see products demoed in their unique circumstances. Companies can spin up these custom environments to give customers an authentic look at how applications will behave in their unique use case.</li>



<li>Innovation and R&amp;D: Companies can provide developers more freedom to experiment and build using easily replicated environments that pass quality controls. Developers utilize simple controls to unlock a brand-new sandbox.</li>
</ul>



<h3 class="wp-block-heading">Environment-as-a-Service bridges the gap between infrastructure and expertise</h3>



<p>Environment-as-a-Service allows companies to add more participants without losing track of who has what version. It can improve the development cycle by removing one of the most common bottlenecks and provides companies with a quality testing ground to ensure that each application goes to deployment in its best iteration.</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/Elizabeth-Wallace-RTInsights-141x150-1.jpg" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/elizabeth-wallace/" class="vcard author" rel="author"><span class="fn">Elizabeth Wallace</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>Elizabeth Wallace is a Nashville-based freelance writer with a soft spot for data science and AI and a background in linguistics. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain &#8211; clearly &#8211; what it is they do.</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">1980</post-id>	</item>
		<item>
		<title>You&#8217;ve Migrated to the Cloud, Now What? 4 Critical Cost-Saving Practices</title>
		<link>https://www.clouddatainsights.com/youve-migrated-to-the-cloud-now-what-4-critical-cost-saving-practices/</link>
					<comments>https://www.clouddatainsights.com/youve-migrated-to-the-cloud-now-what-4-critical-cost-saving-practices/#respond</comments>
		
		<dc:creator><![CDATA[Nitha Puthran]]></dc:creator>
		<pubDate>Tue, 25 Oct 2022 13:42:34 +0000</pubDate>
				<category><![CDATA[Migration]]></category>
		<category><![CDATA[cloud migration]]></category>
		<category><![CDATA[containerization]]></category>
		<category><![CDATA[DevOps]]></category>
		<category><![CDATA[multi-cloud]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=1945</guid>

					<description><![CDATA[Migrating to the cloud has enormous potential but only if companies have a clear process.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/10/Depositphotos_277654968_S.jpg" alt="Migrating to the cloud has enormous potential but companies need a clear process." class="wp-image-1946" width="750" height="563" srcset="https://www.clouddatainsights.com/wp-content/uploads/2022/10/Depositphotos_277654968_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2022/10/Depositphotos_277654968_S-300x225.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2022/10/Depositphotos_277654968_S-768x576.jpg 768w" sizes="(max-width: 750px) 100vw, 750px" /><figcaption>Migrating to the cloud has enormous potential but only if companies have a clear process.</figcaption></figure></div>


<p>In an age of rapid innovation and digital transformation, more companies are starting to see the real benefits of migrating their systems and applications to the cloud. Cloud is arguably the most important component of any company&#8217;s digital journey. However, moving from a traditional data center environment to the cloud can be daunting. Where do you begin? What vendors and partners should you work with? How do you meet business goals with a cloud migration while navigating the constraints of a legacy tech stack?</p>



<p>Migrating to the cloud began in earnest more than a decade ago, but recent recession and inflation fears have prompted even more companies to get off the fence.&nbsp;<a href="https://www.gartner.com/en/newsroom/press-releases/2021-11-10-gartner-says-cloud-will-be-the-centerpiece-of-new-digital-experiences" target="_blank" rel="noreferrer noopener">According to Gartner</a>, the ongoing pandemic and the surge in digital services are making cloud the centerpiece of new digital experiences. Over 85% of organizations will embrace a cloud-first principle by 2025. Or more simply put, &#8220;There is no business strategy without a cloud strategy.&#8221;&nbsp;</p>



<p>While the benefits of the cloud are clear, companies are finding that it&#8217;s not a &#8220;one-size-fits-all&#8221; proposition. The uniqueness and complexity of every enterprise, coupled with the current challenging talent and economic landscape, seems like a daunting task.</p>



<p>There are plenty of missteps to make during a migration – from not fully understanding the investment of time and money involved, to attempting to move the largest, most complex systems first, rather than starting with simpler ones. Therefore, companies need to work with partners that can provide a comprehensive cloud offering backed by 360-degree partnerships with cloud providers, from training, development, certification, and managed services. This is also why companies need to employ outcome-based models for cloud migration from the start to minimize disruption to business operations and ensure business outcomes.&nbsp;</p>



<p><strong>See also:</strong> <a href="https://www.clouddatainsights.com/extending-data-warehousing-to-the-cloud/" target="_blank" rel="noreferrer noopener">Extending Data Warehousing to the Cloud</a></p>



<h3 class="wp-block-heading">Best Practices of an Effective Cloud (or Multi-Cloud) Migration</h3>



<p>Many companies don&#8217;t have the time or expertise for a cloud migration process. Some even find that they&#8217;re spending more money on the cloud. Managed Service Providers (MSPs) are often called in to assist and can even help navigate multi-cloud migration. Other than cloud MSPs, here are four other considerations for optimizing costs, both during and after migration:</p>



<h4 class="wp-block-heading">1. Migration&nbsp;</h4>



<p>The early days of migrating to the cloud saw &#8220;lift-and-shift&#8221; models (like old data center moves), where applications went to the cloud in the same structure they were in before.&nbsp;</p>



<p>It is one of the more expensive ways for companies to operate in the cloud. Without leveraging cloud-native services, they&#8217;ll spend more time and money on basic operations and can&#8217;t quickly scale up or down. The cloud has an unlimited supply of computing resources, so companies that choose to optimize their migration strategy with cloud-native services will save on time, money, and performance issues down the road.</p>



<h4 class="wp-block-heading">2. Containerization</h4>



<p>A step beyond leveraging cloud-native services is to move beyond virtual machines (servers); it&#8217;s more efficient to extract existing applications from servers and modify them to run natively as cloud containers.&nbsp;<a href="https://cloud.google.com/learn/what-are-containers" target="_blank" rel="noreferrer noopener">Containers</a>&nbsp;are software packages containing all the dependencies and configuration information needed to start up quickly and run efficiently on the cloud. With auto-scaling, the application can scale to meet demand peaks. Later, container instances reduce when demand goes down, optimizing spend, keeping users/customers happy while avoiding idle infrastructure.&nbsp;&nbsp;</p>



<h4 class="wp-block-heading">3. DevOps&nbsp;</h4>



<p>Historically, product development and operations teams have been siloed. Development would build applications and then hand off to operations to deploy on production servers.&nbsp;<a href="https://aws.amazon.com/devops/what-is-devops/#:~:text=DevOps%20is%20the%20combination%20of,development%20and%20infrastructure%20management%20processes." target="_blank" rel="noreferrer noopener">DevOps combines these teams</a>&nbsp;into a single process. Cloud adoption and DevOps have great synergies. DevOps brings a lot of automation around building and deploying applications. In partnership, the cloud provides modern infrastructure that is self-service oriented and can scale at the pace the organization needs. While continuous build and deploy (CI-CD) focuses on automation around App, Infrastructure-as-Code (IaC) focuses on automation of (Cloud) infrastructure – initial creation, ongoing maintenance and eventual decommission.&nbsp;</p>



<p>All this automation enables organizations to develop and update products more frequently with better quality and seamlessly using DevOps and a templated approach. It has now become somewhat easier to ensure that security and regulatory requirements are met when new infrastructure is deployed.&nbsp;&nbsp;</p>



<h4 class="wp-block-heading">4. Environment Management&nbsp;</h4>



<p>The cloud is an enormously dynamic environment, and it&#8217;s easy to spin up costly resources. This is where cloud Financial Operations (or &#8220;FinOps&#8221;) play a role.&nbsp;<a href="https://www.finops.org/introduction/what-is-finops/" target="_blank" rel="noreferrer noopener">FinOps is the practice of bringing cross-functional financial accountability to the cloud</a>. It enables engineering and business teams to make the best use of cloud resources. They also ensure that unused and abandoned resources are not inflating cloud run rates. Much like how DevOps breaks down silos, FinOps is all about &#8220;empowering engineering teams to deliver better features, apps, and migrations. In addition, it facilitates effectively managing the costs.&#8221;&nbsp;</p>



<h3 class="wp-block-heading">Exploring New Heights When Migrating to the Cloud</h3>



<p>The world is well beyond discussions over &#8220;if&#8221; companies should make the cloud a key component of their infrastructure.&nbsp;<a target="_blank" href="https://www.idc.com/getdoc.jsp?containerId=prUS48208321" rel="noreferrer noopener">IDC estimates</a>&nbsp;that global cloud spending (including hardware, software, supply chain, and MSPs) will surpass $1.3 trillion by 2025. Those companies still in migration mode must now focus on fine-tuning, optimizing, and long-term outcomes because there&#8217;s no sign of the clouds parting anytime soon.</p>



<p></p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/10/Nitha-Puthran.jpeg" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/nitha-puthran/" class="vcard author" rel="author"><span class="fn">Nitha Puthran</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p><strong><a href="https://www.linkedin.com/in/nitha-puthran-0b8375/">Nitha Puthran</a></strong> is Senior Vice President, responsible for the Cloud, Infrastructure &amp; Security service lines at <strong><a href="https://www.persistent.com/">Persistent Systems</a></strong>. Nitha has close to two decades of demonstrated success spanning core infrastructure and cloud services, managed data center services and digital transformation. She has been instrumental in leading and implementing complex non-linear initiatives for key clients focused on reducing cost of operations and providing excellent client experience. She is responsible for driving key CXO level business relationships and advisory for Persistent’s clients. Prior to Persistent, Nitha led the Global Infrastructure and Cloud business for BFSI vertical at Wipro. Subsequent to her role at Wipro, Nitha worked at Avanade as a Managed Services Business Executive helping them in transforming engagement models. Nitha has a bachelor’s in Engineering from the University of Mumbai.</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">1945</post-id>	</item>
		<item>
		<title>What GitOps Means for the Cloud</title>
		<link>https://www.clouddatainsights.com/what-gitops-means-for-the-cloud/</link>
					<comments>https://www.clouddatainsights.com/what-gitops-means-for-the-cloud/#respond</comments>
		
		<dc:creator><![CDATA[Elizabeth Wallace]]></dc:creator>
		<pubDate>Fri, 22 Jul 2022 13:03:21 +0000</pubDate>
				<category><![CDATA[Governance]]></category>
		<category><![CDATA[cloud governance]]></category>
		<category><![CDATA[DevOps]]></category>
		<category><![CDATA[GitOps]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=1427</guid>

					<description><![CDATA[GitOps could help companies simplify cloud management by applying basic DevOps principles to infrastructure.]]></description>
										<content:encoded><![CDATA[
<figure class="wp-block-image size-full"><img decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/07/Depositphotos_206133146_S.jpg" alt="" class="wp-image-1428"/><figcaption>GitOps uses open-source version control system Git to provision cloud infrastructure.</figcaption></figure>



<p>As more companies adopt a hybrid cloud model or migrate fully to cloud services, they need new methods for management. Traditional, manual infrastructure will swiftly become unsustainable, and the latest application of DevOps offers a solution. GitOps uses Git—a free, open-source version control system for handling all sizes of projects—to automate and provision infrastructure. And this is why companies may want to pay attention.</p>



<h3 class="wp-block-heading">Why GitOps is becoming more popular</h3>



<p>DevOps emerged as a set of best practices for application development. It provided version control, compliance and collaboration, and continuous integration/continuous delivery/continuous deployment (CI/CD) tooling. Despite the DevOps influence on software development, infrastructure remains largely manual.</p>



<p>This was fine when infrastructure was simple, controlled, and on-premises. As data expanded and companies moved beyond the traditional network edge, managing a complex cloud/hybrid cloud environment is beyond manual control.</p>



<p>First created and shared <a href="https://www.infoworld.com/article/3642533/weaveworks-launches-first-enterprise-gitops-platform.html">by Weaveworks</a>, GitOps uses the same principles of DevOps but applies them to the infrastructure itself. Using Git pull requests, users can verify and deploy infrastructure changes. Git becomes a single source of truth through configuration files stored as code. Any pull requests modify the Git repository, syncing live infrastructure automatically.</p>



<p>Traditionally, systems administrators modified and deployed through a series of manual actions executed over physical server racks or through cloud provisioning API. Sharing and collaboration weren’t the norm; finding documentation could be nearly impossible if one administrator left.</p>



<h3 class="wp-block-heading">The benefits of GitOps</h3>



<p>GitOps offers several benefits for teams struggling to maintain infrastructure.</p>



<h4 class="wp-block-heading">Easy to obtain, open-source tool</h4>



<p>Git is already a common tool for developers, and shifting infrastructure provisioning isn’t a challenge. There’s a good chance someone (or many someones) is already familiar with Git and could become multi-functional.</p>



<h4 class="wp-block-heading">A single source of truth</h4>



<p>The biggest challenge with infrastructure is that administrators often cobble together custom scripts and configurations. When something breaks, it’s a significant obstacle to responding, especially if that administrator is no longer involved. GitOps leverages version control so that all team members can track changes, review audit trails, and update documentation.</p>



<h4 class="wp-block-heading">Increased collaboration thanks to transparency</h4>



<p>Teams can use Git to experiment with and deploy new configurations. If they don’t go well, teams can revert back using the Git repository. In addition, a central code repository allows teams to review codes, record commentary, and so on. The entire infrastructure team can participate in monitoring and building.</p>



<h3 class="wp-block-heading">Why the cloud is a natural partner</h3>



<p>GitOps allows companies to standardize processes formerly in the realm of manual, piecemeal updates. As companies systematize everything, GitOps can improve both consistency and reliability within the environment.</p>



<p>GitOps is environment agnostic, making it well-suited to the cloud and hybrid cloud environments. Git manages all parts of the system—it provides the foundation for cloud systems. When these systems experience true consistency, it becomes more possible to scale. GitOps gives operators a way to manage the complexity of cloud systems. They’re able to see deployments across platforms and quickly address challenges through a logical, streamlined documentation trail.</p>



<p>GitOps could also help reduce some of <a href="https://www.clouddatainsights.com/are-cloud-costs-and-sprawl-casting-a-shadow-how-finops-can-help/">the hidden costs</a> of moving to the cloud. Companies don’t need to grapple with vendor lock-in to start, and with the common familiarity of Git, in-house talent might be able to take over more quickly. And its very nature allows companies to manage ever-changing infrastructure with minor disruptions.</p>



<p>GitOps also address security through increased transparency and better management. Removing manual tasks lessens the risk of human error or oversight. It provides audit trails for everything that’s happened or changed within the infrastructure, and an improved encryption/approval process within repositories could help reduce the attack surface.</p>



<h3 class="wp-block-heading">Challenges to consider before adoption</h3>



<p>GitOps is a process change, meaning everyone on board must begin thinking about infrastructure processes in a new way. It requires buy-in, but luckily there’s a good chance some employees may already be familiar with the process.</p>



<p>For engineering teams not used to collaboration or approval processes, GitOps may seem unnecessarily slow or burdensome. This is because developers will introduce a change through Git requests, and those requests will go through an approver. This committee-style approval process may take some getting used to as teams shift to automation.</p>



<p>In addition, while GitOps makes it easier for documentation to happen, team members must still record what’s going on every time they make a change request. An engineering team or infrastructure manager used to manual processes may require some time to get used to this new documentation.</p>



<p>For some, GitOps is a simple rebranding of existing continuous delivery principles. Because it was originally a deployment of best practices from a startup, companies must consider if GitOps principles will actually work within the company&#8217;s boundaries&#8211;cutting and pasting may not be the automatic best route to simplify cloud operations. However, careful consideration before launching GitOps could help decision makers adapt it to their specific operations targets.</p>



<h3 class="wp-block-heading">GitOps and cloud operations still make good partners</h3>



<p>While the definition of GitOps may differ slightly depending on who you talk to, the version control capabilities are a natural fit for cloud operations. These systems introduce complexity, and GitOps exists to reduce that same complexity. Together, they help build a manageable system that reduces manual processes and increases documentation.</p>



<p>GitOps won’t replace DevOps. Instead, it moves DevOps into the realm of infrastructure, giving companies a better handle on their cloud operations. Any solution that facilitates provisioning even with a hybrid cloud environment offers companies an edge as they make the digital transformation shift.</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/Elizabeth-Wallace-RTInsights-141x150-1.jpg" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/elizabeth-wallace/" class="vcard author" rel="author"><span class="fn">Elizabeth Wallace</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>Elizabeth Wallace is a Nashville-based freelance writer with a soft spot for data science and AI and a background in linguistics. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain &#8211; clearly &#8211; what it is they do.</p>
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