[{"data":1,"prerenderedAt":718},["ShallowReactive",2],{"/en-us/blog/lm-sre-shadow/":3,"navigation-en-us":35,"banner-en-us":464,"footer-en-us":481,"Laura Montemayor":691,"next-steps-en-us":703},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"seo":8,"content":16,"config":25,"_id":28,"_type":29,"title":30,"_source":31,"_file":32,"_stem":33,"_extension":34},"/en-us/blog/lm-sre-shadow","blog",false,"",{"title":9,"description":10,"ogTitle":9,"ogDescription":10,"noIndex":6,"ogImage":11,"ogUrl":12,"ogSiteName":13,"ogType":14,"canonicalUrls":12,"schema":15},"Shadowing a Site Reliability Engineer","On-call through the eyes of a software engineer. Read Laura's week shadowing a Site Reliability Engineer","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749679120/Blog/Hero%20Images/sre-shadow-week.jpg","https://about.gitlab.com/blog/lm-sre-shadow","https://about.gitlab.com","article","\n                        {\n        \"@context\": \"https://schema.org\",\n        \"@type\": \"Article\",\n        \"headline\": \"Shadowing a Site Reliability Engineer\",\n        \"author\": [{\"@type\":\"Person\",\"name\":\"Laura Montemayor\"}],\n        \"datePublished\": \"2020-04-13\",\n      }",{"title":9,"description":10,"authors":17,"heroImage":11,"date":19,"body":20,"category":21,"tags":22},[18],"Laura Montemayor","2020-04-13","\n{::options parse_block_html=\"true\" /}\n\n## A day in the life of a SRE at GitLab with Laura Montemayor\n\nHi! I’m [Laura Montemayor](https://gitlab.com/laura.Mon), a Frontend Engineer in GitLab’s [Monitor:Health Group](https://about.gitlab.com/handbook/engineering/development/ops/monitor/respond/). Monitor is one the [DevOps lifecycle stages](https://about.gitlab.com/stages-devops-lifecycle/) that comes after you’ve configured your production infrastructure and have deployed your application to it. We work on features that help you monitor metrics and Kubernetes, track errors, manage incidents, and more.\n\n_If you’re curious about our team, you can check out our [direction page](/direction/monitor/) to see what’s on the roadmap._\n\nA few weeks ago, I had the opportunity to  shadow our SREs, which was pretty exciting\nfor me, as it is monitoring in action.  An SRE is a **Site Reliability Engineer**,\nwho is responsible for keeping all user-facing services and other GitLab production\nsystems running smoothly.  \n\n_You can learn all about them in [our\nhandbook](https://handbook.gitlab.com/job-families/engineering/infrastructure/site-reliability-engineer/)._\n\n**Here are some of my general takeaways from that week:**\n\n#### Less is more when it comes to tooling\nI’ve had non-remote friends ask me what communications tools we use at GitLab, and\nthey are sometimes surprised that it’s not a long list. In a way, I had the same\nexpectation for our SREs and their tooling; I had visions of them all buried underneath monitors, with screens showing moving graphs, stats, logs - the works!. But SREs use\nthe same tools everyone at GitLab uses for communication - GitLab issues, Slack and\nZoom. The workflow is pretty straightforward; the on-call SRE gets pinged on\nPagerDuty, which also sends an alert to a Slack channel, and everything is discussed\neither there or in an issue. True to our [transparency](https://handbook.gitlab.com/handbook/values/#transparency) value,\neveryone at GitLab has access to the channels and the issues, and most of these issues are public.  \n\n_If you are interested in learning more about SREs and the tooling they use (and\nmore!), check out my [teammate’s blog\npost.](/blog/sre-shadow/)_\n\n![sre alert flow](https://about.gitlab.com/images/blogimages/sre-alert-flow.png)  \n_MT = Monitoring Tool_\n\n#### Managing the level of noise is a huge challenge\nDuring the time I shadowed, I probably saw an alert every 5 or so minutes.\nAnd this was during their so called “quiet time”! At first, it seems overwhelming to be alerted so often,\nand everything looked serious and actionable to me. _Queue latency outside of SLO?\nFilesystem will be full SOON?_ I panicked. However, a lot of these alerts are warnings\nand don’t all turn into incidents; but even if they are warnings, sometimes they\nmerit some investigation and discussion, since almost no alert can be truly ignored.\n\n##### Examples of alerts that can usually be ignored:\n1. **CPU/Memory usage that just stepped over 90%** - This can be ignored (but an eye\nshould be kept on it) because the prediction algorithms for usage often raise an\nalert prematurely. The usage normally falls to safe levels or won’t cause an issue\nfor a few more SRE shifts.\n2. **Abuse detection** - This can give a lot of false positives which are not\nnecessarily an incident, like abuse being detected when a project’s pipeline is used\nexcessively.\n\n#### Incidents don’t happen as often as I thought\nSo even though there are a lot of alerts, I was surprised to find the majority of them don’t actually turn into incidents. There was a part of me who wanted to experience an incident, since I\nthought going into a situation room and resolving it would be really exciting. But\nthere were only two incidents, and one of them was resolved straight away and the\nother one was handed over for further investigation. None of them were disruptive to\ncustomers though, so all in all, I figure GitLab must be pretty stable 💪\n\n#### Monitoring is hard (no surprise there!)\nExperience and domain knowledge certainly help when it comes to sifting through the\nnoise, but it doesn’t make it easy.  A lot of alerts happen because they are often\nbased on inflexible Boolean logic or some arbitrary threshold.\nFor example: we got an alert for a spike in the redis-cache latency Apdex.  We\nchecked the Grafana dashboard and realized it was a one off spike in latency, so it\nwas fine for the time being. But it was one more thing to keep an eye out for, and\nthe intermittent spiking kept alerting us, which added more cognitive noise. I can’t even begin to imagine the horror of trying to effectively monitor with a bunch of different tools. This  is why I love\nthe idea of a single app for all your needs 😉\n\n#### Communication is key\nOne thing that helps immensely with monitoring and incident management is\ncommunication. It is one of our [core values](https://handbook.gitlab.com/handbook/values/#collaboration) at GitLab after all, seeing as we are an\nall-remote, async team. If the SRE who is on-call cannot resolve the issue straight\naway, they can just ping other SREs on Slack and someone will be available to help.\nIt’s the advantage of being an async team - there’s always someone available in\nalmost every single timezone! It also means that even if you’re not on the SRE team\nand you’re working on something that will start firing off alerts, you should\ncommunicate with the SREs to let them know. For example: some changes were made in\nthe Pages API, which were rolled out to 20% of the domains. This caused an increase\nin alerts, but since it was properly communicated, the SRE on call could be assured\nthat these alerts were fine to ignore. There was no way of turning these alerts off\nunfortunately, since the rigidity of the tools doesn’t allow it.  \n\n[Here’s the issue](https://gitlab.com/gitlab-com/gl-infra/production/-/issues/1734), if you’re curious.\n\n#### We love issues 🧡\nAt GitLab, we love writing everything down in issues, which helps a lot with incident\nmanagement. Every time an SRE changes shifts, they write a handover issue with a\nsummary of what alerts/incidents are ongoing or resolved, etc. Check out [this\nexample](https://gitlab.com/gitlab-com/gl-infra/on-call-handovers/-/issues/413).\nEvery time an alert actually becomes an incident, the first step is always to\nresolve it, since it affects our customers. After that, an issue is created to\ncollaboratively do a root cause analysis and hopefully prevent it from happening\nagain. Keeping record of all of the incidents is really helpful for context and\nresolution of future incidents.\n\n#### There must be collaboration\nOur SREs who are on-call do not work in isolation, and even though they are the first\npoint of contact for alerts, it’s not expected that they solve everything themselves.\nSometimes things can’t be solved in the moment, like the example below.  \n\n**Incident:** AlertManager is failing to send notifications  \n**Why weren’t we able to resolve it?** We don’t have visibility when Alertmanager doesn’t\nwork, as we don’t have logs or graphs to for it.  \n**So what now?** We first checked to see if there was a similar or a linked issue, and\nthere was. After that, we made an issue for it, linked the other issue, assigned a\ndomain expert, and went from there.  \n\n[Here’s the issue.](https://gitlab.com/gitlab-com/gl-infra/production/-/issues/1707)\n\n#### Monitoring is a growing field\nGiven the imperfect nature of monitoring, it’s only natural that the field is\nconstantly evolving and growing. At GitLab, we recently created a [Scalability team](/handbook/engineering/infrastructure/team/scalability/),\nwhich will help curate our monitoring and alerting. They will frequently update the\ncriteria to generate alerts, which will make the whole process more manageable. My\nteam is responsible for building the features to help monitor and manage incidents,\nand we’re currently working on features which will help with our SREs workflow. If\nyou’re interested, check out our [Ops Section Product Vision](/direction/ops/) for more details. You can also check out the [reliability guide](/handbook/engineering/infrastructure/team/reliability/) for\na more in-depth and robust look at what our SREs do.  \n\n[Join us](/jobs/) at GitLab! 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