GitLab vs. Splunk Observability Cloud

In general it's a good product with a huge number of features. It can do CI/CD checks, deployment, repo hosting, integrations etc. A lot of it can be managed from just the UI but also has an ok API. It does tend to release new features semi-often too which is nice. It can have a steep learning curve for certain features so not a starter-friendly vendor, but great for most businesses.

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Its great if you need real-time visibility across complex or regulated environments. Also strong for hybrid or multi-cloud setups where uptime, observability and fast IR are required. It’s probably overkill for smaller teams or environments that don’t have constant changes or compliance reporting needs. It's expensive and has a steep learning curve. Also, in my opinion, do not get yourself into a consumption based model. Costs can certainly get out of control quickly.

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• GitLab excels in managing code versions, allowing easy tracking of changes, branch management, and merging contributions.
• It helps maintain code stability and reliability, saving time and effort in the development or research workflow.
• Powerful code review features, enabling collaboration and feedback among team members.
• Robust project management features, including issue tracking, kanban boards, and milestones.

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• The first one is its Kubernetes container monitoring.
• I really like this features because as we know how much K8s is vast and to manually monitor each part of the Kubernetes it takes so much time but Splunk Observability Cloud makes it easier. And even once we integrate K8s with Splunk Observability Cloud it gives us some prebuilt dashboards which gives holistic view of our Cluster and its nodes, pods, etc.
• The dashbaord feature of Splunk Observability Cloud, it gives us full flexibility to customize our dashboard with a wide range of predefined chart types.
• Now it also supports OTEL, which is a plus point for observability. As now everyone is moving towards Otel and in current market there are only few tools who supports OTEL based integrations, Splunk Observability Cloud is one out of them.

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• CI variables management is sometimes hard to use, for example, with File type variables. The scope of each variable is also hard to guess.
• Access Token: there are too many types (Personal, Project, global..), and it is hard to identify the scope and where it comes from once created.
• Runners: auto-scaled runners are for the moment hard to put in place, and monitoring is not easy.

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• You can use table-like functionality to generate dashboards, but these queries are heavy on the system.
• It could be easier to give insight into what type of line parsing is used for specific documents in a company-managed environment and/or show ways to gain the insights needed.
• I would like to see ways to anonymize specific data for shared reports without pre-formatting this in a dashboard on which reports could be based.

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I really feel the platform has matured quite faster than others, and it is always at the top of its game compared to the different vendors like GitHub, Azure pipelines, CircleCI, Travis, Jenkins. Since it provides, agents, CI/CD, repository hosting, Secrets management, user management, and Single Sign on; among other features

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Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net

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- As a combination of features and products, GitLab is a really great tool for developers. - Also, it comes with both light and quick changes in a web browser version, as well as pro work in VS Code mode. However, in certain areas, such as large-scale issues/incidents, management can be improved.

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When there is an issue, it’s a win if one can easily identify the root cause. To do the same, it should allow the user to dig deep with multiple data points and compare the data and identify the anomaly. In this use case, it’s good to drive from Splunk 011y.

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I've never had experienced outages from GItlab itself, but regarding the code I have deployed to Gitlab, the history helps a lot to trace the cause of the issue or performing a rollback to go back to a working version

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GItlab reponsiveness is amazing, has never left me IDLE. I've never had issues even with complex projects. I have not experienced any issues when integrating it with agents for example or SSO

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At this point, I do not have much experience with Gitlab support as I have never had to engage them. They have documentation that is helpful, not quite as extensive as other documentation, but helpful nonetheless. They also seem to be relatively responsive on social media platforms (twitter) and really thrived when GitHub was acquired by Microsoft

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Splunk support is very quick and efficient. Pre-sale specialists are very skilled and available.

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Follow a training before starting.

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GitHub is an inferior product from most points of view. We had to use it and the teams finds no positives about it. Everything is a downgrade from our previous GitLab solution. GitLab CI\CD is vastly superior to workflows, for example doing a manual node is just "when : manual" in GitLab while you have to do clickops in GitHub to achieve the same. No overview of code in branches is a minus when we tried to figure out what our colleagues are trying to merge as it looked off.

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Splunk Infrastructure Monitoring provides far superior options for anybody using a complex hybrid multi-cloud environment and allows both your SOC and NOC to work together on the same data while driving their own insights. We found other products are still in the old world view of servers and agents residing together within a single data centre, but modern apps are no longer like this.

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I think is very well designed, and like any VCS it works as intended

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• GitLab cut down our spent on container, package and infrastructure registry
• Best thing is we can now have everything in single platform which cost effective too
• Quality of support is really good and they do have emergency support team as well which is great

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• Significantly reduced the MTTR (Mean Time To Recovery), which in turn has improved the end-user experience tremendously.
• Meets compliance requirements of security policies, audit, regulation, and forensics.
• Helps us to track/manage the resource usage on our cloud instances which has a direct implication on the recurring cost.

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