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Imagine you wish to update an already running application to its latest version; usually, these factors should be kept in mind to ensure a successful rollout:
- How to minimize application downtime if it arises.
- Manage and resolve incidents efficiently to cause minimal impact on users.
- How to handle failed deployments.
- Learn how to reduce errors within people and processes to ensure predictable, repeatable deployments.
- Your business objectives will determine the deployment method you select. You should deploy changes without downtime or to a specific environment or subset of users before making a new feature available to all. The methodologies discussed here are based on specific goals you must meet to make a deployment successful.
This document was intended for DevOps and system administrators responsible for developing deployment/release strategies for various applications, frameworks, or systems.
Deployment Strategies
Only some deployed services will immediately become visible to users; any modifications made during development might only become evident after the release of the application.
Deployment and release, which happen simultaneously when releasing, begin immediately upon production traffic flowing on production traffic beginning flow after the new version was made life.
There are deployment patterns that enable you to provision multiple versions in parallel so you can determine which version receives each incoming request using these strategies; more details on deployment, release, and other concepts can be found by reading Kubernetes: the Challenges of Continuous Software Delivery by Kubernetes: Continuous Software Delivery by Kubernetes by reading Kubernetes:
For additional insights regarding deployment-related topics, read Kubernetes: the Challenges of Continuous Software Delivery, published by Kubernetes! For additional insights, read Kubernetes: the challenges of Continuous Software Delivery.
Read Kubernetes: the challenges of Continuous Software Delivery by Continuous Software Delivery by Richard CJ Cleator Eric Thomas CJ CJ Container Orchestration! Read Kubernetes CSD by Richard Czars or read Kubernetes CSD by Continuous Software Delivery from Richard CJ CD or read "Continuous Software Delivery".
Automating software deployment with these patterns allows for the smooth implementation of any new program or update.
Your goals should dictate which approach best meets them.
Recreate Deployment Pattern
Replicating an application involves completely scaling back its original version for use with its successor version.
Key Benefits
Simple is one of the benefits of taking this approach; one advantage of recreating is its effortless nature.
Considerations
Update methods generally involve downtime; applications that can withstand outages or maintenance windows don't seem affected by it.
However, choose another deployment strategy if your software needs to meet strict service level agreements and high availability standards.
Rolling Update Deployment Pattern
Rolling update deployment is a form of software modification in which only certain application instances running are updated at one time rather than all simultaneously.
Window size refers to the number of updates made simultaneously during this deployment method, such as rolling updates with one application instance being updated simultaneously.
You may expand or reduce this size based on how many clusters there are in total.
Your app can be updated in different ways with rolling updates:
- Before downgrading to an older version, an "upgrade surge" should occur where more instances are launched of applications simultaneously.
- Your goal should be to set a maximum limit for scaling multiple instances simultaneously while others become unavailable. You can do this by specifying their maximum parallel scaling number in parallel scaling mode.
Key Benefits
- No downtime updates of deployment targets can be implemented seamlessly by incrementally altering them two at a time or one after each release of your app version without impacting traffic flow or altering visitor navigation patterns. Traffic directed toward updated deployment targets automatically becomes active once version 2.0 or greater has been released and is directed directly.
- Deployment risk can be reduced. By rolling out incremental updates, instabilities should only impact a fraction of users.
Considerations
- Reversing gradually. To safely roll back, stop replicas if their rollout becomes unstable, redeploy your old version, and gradually implement this change back process again. A rollback must take place gradually over time to maintain continuity in operations.
- Backward compatibility. Users could be directed between new and old codes arbitrarily, so ensure your new deployment will be backward compatible - in other words, capable of handling and reading data stored from both versions. These data might reside on disk or even be part of user sessions.
- Session Persistence. The load balancer supports stickiness, releasing connections if an application needs session persistence. Furthermore, it is wise to employ session sharing either through replication or session management with a datastore to keep sessions separate from underlying resources.
Blue/Green Deployment Pattern
Your application can be deployed using two techniques - blue/green and red/black. Keep the blue deployment for any instances where you wish to roll back or withdraw it, deploy an updated version of your app in these instances, or as a staging area before the new release is made available.
Key Benefits
- Zero Downtime. Blue/green deployment provides for an effortless switchover with zero downtime.
- Instant rollback. At any point during deployment, traffic can be directed back towards "blue." Your only downtime would be moving it from red back to blue once an issue has been detected.
- Separation of Environment. With blue/green deployments, resources supporting one environment won't be affected by an alternate green one being started up, thus decreasing risks during deployments.
Considerations
- Cost and Overhead. Adopting a blue/green deployment model increases cost and operational overhead by necessitating you to maintain two identical environments.
- Backward compatibility. In both blue and green deployments, data points and stores should be compatible between versions of your application, ensuring they use identical schema and format data stores. It's key that there be backward compatibility if your goal is seamless switching between versions in case of rollbacks.
- Cutover. We suggest draining existing sessions and transactions if you plan to decommission or end your current version gracefully through this step. Your current deployment can be gracefully concluded without disruptions or difficulties.
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Testing Strategies
These patterns validate service stability and reliability over an extended period under realistic concurrency levels and loads.
Canary Test Pattern
Canary testing is a technique of simulating partial deployment to compare its performance against an initial one.
This test pattern involves simultaneously deploying two application versions -- production and Canary -- before splitting traffic to compare performance between them.
You should send some percentage of traffic from production to Canary before measuring its performance against production.
Configuring the Canary involves choosing which metrics will be evaluated, with equal baseline conditions, instead of operating within a production environment.
It is highly advised to perform testing using Canary only in an equal baseline environment versus a production environment for evaluation purposes.
When creating your baseline application, follow these steps to minimize factors that could interfere with analysis, such as caching and long-lived connections.
- Ensure your app's baseline and production versions are 100% identical.
- Do not install a canary before setting up the baseline.
- Verify that baseline deployments (such as several instances, auto-scaling policy and application) match canary deployment.
- The baseline version can provide service to similar traffic as Canary Island.
Canary testing can be implemented using various partitioning techniques to roll out an application in canary tests gradually.
For instance, if users are geographically dispersed, then the initial rollout could begin in one region before expanding across more. More information.
Key Benefits
- Test Live Production Traffic. By simulating real production traffic instead of simulating, an application can be tested against real production environments more closely and at any desired increment release times - Canary requires sufficient traffic to detect issues quickly.
- Redirecting user traffic back to an earlier version can quickly return it. Doing this allows for fast rollback.
- Canary releases allow for zero downtime by seamlessly routing live production traffic between applications without experiencing downtime.
Considerations
- Roll Out Slow. Incorporating canary tests for each incremental release may slow the overall rollout. Canary tests typically last several hours.
- Canary testing requires monitoring and observing both your application and infrastructure; it's often an effortful endeavor to implement robust monitoring solutions.
- Sticky sessions and backward compatibility. Similar to rolling updates, canary testing may pose risks related to backward compatibility and persistent sessions due to multiple application versions being present in an environment where canary testing occurs.
A/B Test Pattern
With A/B tests, putting your hypothesis through its paces is easy by employing different implementation strategies.
Results of A/B tests should inform business decisions rather than serve only as predictions.
Routing rules involve numerous variables, including browser versions, user agents, geolocation and operating systems.
After carefully considering and measuring all possible versions, update your production environment using the one with superior characteristics.
Key Benefits
An A/B test is the optimal way to assess an application's functionality, with its deployment patterns serving as the ideal means of doing this safely and reliably.
You can tailor each feature test audience as desired while monitoring any significant statistical variations between iterations 1 and 2.
Considerations
- Setup can be complex. A/B testing requires selecting an adequate sample size to demonstrate that one version of your test is superior. Precalculate your sample size using something such as an A/B Test Sample Size Calculator before running your experiment over enough time that it will reach statistical significance.
- Validity of Results. False positives, biased sampling practices or external influences such as seasonality or marketing campaigns could compromise results and alter them dramatically.
- Observability. Monitoring and troubleshooting multiple A/B tests on traffic that overlaps can be complex. Distributed tracing becomes important when you compare product pages A to B or checkout pages C to D.
Test Pattern for Shadow
Canary testing and other sequenced experimentation techniques can expose early test subjects to subpar applications during early phases.
To protect customers against such exposure, using techniques offline - like simulation - such as canary testing may help manage this risk more effectively; however, these offline techniques cannot verify application improvements since users cannot interact with it directly.
Shadow testing occurs when you run and deploy an earlier version concurrently without informing users.
Requests received are replicated and played back in a test environment to simulate customer usage scenarios in real-time or asynchronously by replaying production traffic to test-run the newly introduced service.
Shadow testing should never produce side effects that alter either production environments or users' states in any significant manner.
Shadow tests must remain free from adverse side repercussions, which might significantly alter them.
Key Benefits
- Zero production impact. Because shadow data processing services handle it independently from production services, any bugs affecting output won't impact it because traffic will be duplicated.
- As with production traffic, traffic shadowing allows you to test backend features using production traffic. By employing tools such as Diffy and similar programs such as QIRC to shadow production traffic and shadow the behavior of services like yours against real-time production traffic flows in real-time production environments - traffic shadowing gives you access to real-time measurements of performance metrics like application versions' performances, errors, exceptions and results parity for performance benchmarking purposes.
- Traffic Shadowing reduces deployment risks. Using canary testing or another testing methodology in combination with traffic shadowing, features can be tested before being released to more users as more time goes on - until they meet both stability and performance criteria for full deployment of an app or website.
Considerations
Side Effects. Traffic shadowing requires you to exercise extreme care when handling services that change state or interact with each other; for instance, shadow-testing a payment service on an online shopping platform could force customers to pay twice for their orders if testing involves mutations or risky interactions; we suggest using virtualization tools like Hoverfly in this regard to protect customers.
Costs and Overheads. Setting up shadow testing can be intricate; similarly, blue/green deployments incur costs due to running both environments simultaneously.
Selecting the Best Strategy
Various approaches are available for releasing and deploying applications, each offering advantages and drawbacks; your business's needs and requirements will ultimately dictate its path.
Take note of the following:
- What should be your main priority, acceptable downtime and costs? Do you possess the expertise for complex setups such as rollouts/retrofits?
- Can you oversee the testing process or wish to run releases in production traffic to limit negative side effects and ensure stability?
- Do You Want to Test Features with Users? Testing features with users in groups can help your business verify certain hypotheses about itself and test specific hypotheses about its business practices. Control whether those targeted accept an update - mobile device updates require user interaction as they might require extra permissions - is another approach you could take when testing features that could make organizational changes more successful.
- Microservices - are they fully independent in your environment, or do you combine traditional applications and microservices? See Deployment patterns for hybrid and multi cloud environments for further considerations.
- Do the schema changes in this release require any code modifications, and are they complex enough that they should be separated from code changes?
Best Practices
Teams responsible for application development can reduce deployment and testing risks by adopting various best practices:
- Compatibility with Older Versions. When running multiple versions of an application simultaneously, make sure your database remains compatible between versions. A new application version may require altering its database schema, such as adding columns. You will need to modify its schema accordingly to remain backward compatible with an earlier one and gradually remove support of older schema versions until full rollout occurs; decoupling schema updates from code updates is one way of assuring backward compatibility; see parallel changes and database refactoring for more details.
- Continuous Integration/Continuous Deployment (CI/CD). Continuous Integration ensures code from feature branches is only merged with main branches after passing all unit, Integration and dependency tests before merging back to the main branch for merge. Each change made must also be tested before deployment. Code artifacts created through Continuous Integration can then be packaged up by Continuous Deployment for deployment in one or multiple environments; more information on creating such pipelines with Google Cloud can be found by viewing our Building a CI/CD Pipeline Guide.
- Automation. Automating the building, testing, and deployment process of software for continuous application updates to users can make deployment more reliable and efficient. We advise using automation tools like Spinnaker Jenkins TravisCI or Cloud Build for this process to increase reliability and efficiency during deployments.
- Configuration Management and Operating Environments. Various tools like Vagrant and Packer can assist in creating consistent development environments at local development, staging, or production levels. Puppet Chef and Ansible offer configuration management features that automatically automate OS updates or patches in target servers.
- Create a rollback strategy. Should anything happen during deployment, have an actionable plan for rolling back. Spinnaker or Harness, release automation tools, support rollback capabilities, or keep an application backup until the new version works as intended.
- Post-deployment monitoring. Application performance monitoring tools can assist your team in monitoring critical metrics. Set up alert systems when deployment or build failure occurs and roll back deployments that don't pass health checks due to availability issues or error rates.
How to Create and Implement an Outstanding Automation Strategy
Acclimatizing any new method or software requires time and effort; however, its rewards compensate for that investment.
Automating testing processes can drastically enhance software quality while saving time and money.
But automation should be implemented more than just unthinkingly. For optimal software releases, having a strategy in place must also be considered part of this equation.
This article explains how to develop and implement an excellent test automation strategy so your efforts in testing are worthwhile, with quality software reflecting your well-thought-out plan and optimizing the product before use by clients.
1. Unable To Demonstrate Business Value
Teams seeking to implement new solutions such as performance or web-based testing automation often need to spend more time considering the business case of such solutions before investing.
While technology might look great and have great value to businesses, if this technology cannot demonstrate actual ROI, then projects risk cancellation or rejection due to not providing proof of its ROI.
Read More: Why Is Testing Essential in the Development of Software?
2. Vision Problems
Unsettled automated projects often find it challenging to establish a clear vision without some strategy in place, especially as automation projects often veer off course and shift in their direction; for instance, adding or switching out applications as part of their framework or altering technology may become necessary at any point during development.
When this occurs, it can become easy to postpone or cancel projects without knowing their original vision - having one provides an effective means of documenting key questions before acting accordingly.
3. Technology Efficiency Loss
Your business could suffer technology efficiency losses without an articulated test automation strategy. Your chosen automation tool must match up perfectly with the application.
Otherwise, you risk forcing technology into areas where it shouldn't belong and forcing solutions that shouldn't use this specific solution into existence. With planning and documentation of this aspect of testing, efficiency gains could be avoided.
4. Unpreparedness For "Testing Squeeze"
Software development remains a world of testing pressure. To determine what scripts need to be cut first and where one needs a test automation strategy: what scripts need cutting? Which items were the most essential and why? Was there an association between business value and what was tested; with such information, it can be easier to know where or how best to eliminate scripts; one might end up cutting everything and dealing with issues later.
Automation Strategy
Now that we have established its value, look, and purpose, let's focus on the steps needed for successfully implementing a test automation strategy.
Step 1: Define High-Value Tests
First and foremost, we must identify the most critical tests. These should include tests that could potentially put a business out of action if its flow stops working as designed; Knight Capital Group was one such trading company that went from full operation to bankruptcy within 45 minutes due to software issues (an unnoticed high-value test was one reason behind their loss of approx $485Million!).
Work closely with your organization in identifying their high-value tests to understand whether any proposed solutions meet all relevant scenarios; doing this can enable ROI discussions more clearly.
Step 2: Identify Your Risk
Knowing what tests should come first or last is essential when developing and automation strategy.
Testing automation priorities must be set using risk analysis; by adding up the business impact with failure probability, you can calculate its priority or risk level and determine its testing priority or risk rating.
Prioritize items with the biggest business impact and highest likelihood of failure first; place those with minimal business impact but lower risks last in priority - this will aid your testing processes as you decide where to reduce first.
Step 3: Understanding Your Tools And Technology
Know how your overall solution for testing automation will impact your environment before proceeding. Be sure to have access to your account(s), environment(s), APIs, libraries, API calls etc., necessary for communication between the test automation system and application.
Ensure the framework allows a working and robust solution without slowing it down or creating broken tests!
Step 4: Check Your Data Quality
Data errors derail many test automation projects. You could save hours by validating or loading it earlier through your automation framework or running prescripts that validate or load the data before beginning work on the project.
When dealing with large releases or iteration phases, review how your handling of data works to include where and how much is stored and whether there's any retry logic and masking required.
Step 5: Define Your DevSecOps
Your testing automation strategy must account for this aspect.
- Question yourself: Where is my code stored?
- What is Your Deployment Strategy?
- Are the environments in which you operate safe and secure?
- Are the code and libraries you utilize secure?
Conduct a security scan and establish an effective procedure for its implementation.
Step 6: Consider Your Test Environment
Documenting environmental conditions is a complex endeavor. Do you require VPNs and tokens, Launch Boxes? Who manages them and is responsible? Who patches these systems when necessary? Documenting all this will enable new testers to join your company more smoothly while setting up logins - documentation also gives your staff insight into where your code runs at any given moment and ensures that its location can be easily documented.
Step 7: Tag Your Tests
Whether there are 20,000 or 50,000 test scripts, I know which ones belong to the checkout process, the login process and smoke tests." Without tags to mark tests with, identifying their purpose could take considerable effort; to guarantee consistent tagging practices, create an agreement before running tests and enforce it with tags.
Step 8: Test Efficiency
As your testing volume grows, applying similar logic across various testing areas will enable you to save both time and money by decreasing resources used and times dedicated to testing.
When performing unit, automation, manual, and user interface testing simultaneously, having one tester running each type can often save much time; understanding your testing strategy from unit tests through user interface tests can save even more.
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Bottom Line
When developing their strategies, strategies should focus on communication, goals and objectives - not their format.
What will your value proposition be? What's the overall purpose of your technology? And how is its effect going to manifest on people and environments?
Testing requires the assistance of business partners, project managers and product owners who understand your strategy to facilitate decision-making.
They're your ally if any challenges arise while making crucial calls on your behalf as the boss. Make use of your testing automation strategy to invest in cutting-edge technologies and grow your business through innovation - that's the whole point - innovation, growth, and the ability not to have to go backwards.
