AWS CodePipeline is a fully managed continuous delivery service that helps users automate release pipelines. CodePipeline automates the build, test, and deploy phases of the release process every time there is a code change, based on the release model a user defines.
$1
per active pipeline/per month
Azure Pipelines
Score 8.5 out of 10
N/A
Users can automate builds and deployments with Azure Pipelines. Build, test, and deploy Node.js, Python, Java, PHP, Ruby, C/C++, .NET, Android, and iOS apps. Run in parallel on Linux, macOS, and Windows. Azure Pipelines can be purchased standalone, but it is also part of Azure DevOps Services agile development planning and CI/CD suite.
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Splunk IT Service Intelligence (ITSI)
Score 10.0 out of 10
N/A
Splunk supports IT operations analytics with the Splunk IT Service Intelligence premium offering, a software application available to subscribers to Splunk Cloud or Splunk Enterprise log analytics and SIEM platforms.
We have used the GitHub CI/CD. Earlier we were using the Azure Pipelines but after GitHub had their actions, we integrated that for CI/CD. It runs the tests and makes a production build which can be live. GitHub CI/CD is more useful because we have to make script only once then …
I think AWS CodePipeline is a great tool for anyone wanted automated deployments in a multi-server/container AWS environment. AWS also offers services like Elastic Beanstalk that provide a more managed hosting & deployment experience. CodePipeline is a good middle ground with solid, built-in automation with enough customizability to not lock people into one deployment or architecture philosophy.
It is good tool if you are doing continuous improvements in your code and you wish it goes live whenever you push code to GitHub. So integrating Azure Pipeline, it automatically does CI/CD in the background once you push code/merge code and it is live in few minutes. It also does some automated tests if you have wrote scripts
Splunk ITSI is a great tool (and toolbox) for combining together numerous and varied monitoring regimes to bring more holistic analysis and reduce alert fatigue. By leveraging the Splunk ITSI service and KPI modeling regime, ecosystem telemetry can be turned into a more reliable, clearer, high-level perspective on the current state of your components and services.
We have replaced our monitoring platform with Splunk & ITSI, and with the success, it's seen at our organization thus far we would be hard-pressed to pivot to another tool. Frankly, our business partners and application teams love Splunk & ITSI.
Overall, I give AWS Codepipeline a 9 because it gets the job done and I can't complain much about the web interface as much of the action is taking place behind the scenes on the terminal locally or via Amazon's infrastructure anyway. It would be nicer to have a better flowing and visualizable web interface, however.
Splunk IT Service Intelligence (ITSI) is a platform with extended functionality and provides various functionalities which can be utilized to improve the efficiency and accuracy in analyzing the data and detecting the attacks.
Our pipeline takes about 30 minutes to run through. Although this time depends on the applications you are using on either end, I feel that it is a reasonable time to make upgrades and updates to our system as it is not an every day push.
We didn't need a lot of support with AWS CodePipeline as it was pretty straightforward to configure and use, but where we ran into problems, the AWS community was able to help. AWS support agents were also helpful in resolving some of the minor issues we encountered, which we could not find a solution elsewhere.
During POC, pre-planning, and implementation, we have had interactions with numerous folks at Splunk. Everyone from sales & engineering to markets analysts to specific IT component SMEs, and a small professional services engagement to get started. They have all been exceptionally helpful and go above and beyond the call of duty. They actively reach out to ensure success is being realized and find ways to help proactively, instead of having to simply open support cases with the vendor.
CodeCommit and CodeDeploy can be used with CodePipeline so it’s not really fair to stack them against each other as they can be quite the compliment. The same goes for Beanstalk, which is often used as a deployment target in relation to CodePipeline.
CodePipeline fulfills the CI/CD duty, where the other services do not focus on that specific function. They are supplements, not replacements. CodePipeline will detect the updated code and handle deploying it to the actual instance via Beanstalk.
Jenkins is open source and not a native AWS service, that is its primary differentiator. Jenkins can also be used as a supplement to CodePipeline.
We have used the GitHub CI/CD. Earlier we were using the Azure Pipelines but after GitHub had their actions, we integrated that for CI/CD. It runs the tests and makes a production build which can be live. GitHub CI/CD is more useful because we have to make script only once then just by few changes we can deploy it onto Azure, AWS, Google anywhere so we found it more convenient
Splunk has raised itself as a platform not just as a tool unlike other products in the market. If I talk about Moogsoft it also has similar capabilities but Splunk ITSI has more visibility and its GUI is making a different impact on the users. ServiceNow and Splunk are equally capable products however Splunk seems to have more tech-savvy people tools than ServiceNow.
CodePipeline has reduced ongoing devops costs for my clients, especially around deployment & testing.
CodePipeline has sped up development workflow by making the deployment process automated off git pushes. Deployment takes very little coordination as the system will just trigger based on what is the latest commit in a branch.
CodePipeline offered a lot of out-of-the-box functionality that was much simpler to setup than a dedicated CI server. It allowed the deployment process to built and put into production with much less and effort and cost compared to rolling the functionality manually.
Splunk ITSI has reduced the number of alerts exposed to our Network Operations Center by 100x while increasing the context around outages.
Splunk ITSI has increased the accuracy of our incident detection by leveraging the Event Analytics system to weigh the behavior of the many characteristics of each component together instead of independently.
Splunk ITSI has reduced our incident MTTR (mean time to restore) by detecting issues faster, presenting them more clearly, and surfacing the salient details about the underlying issue.
