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Gartner’s IT Infrastructure, Operations & Cloud Strategies Conference (IOCS) is an annual event that attracts ITOps, SRE, and DevOps leaders from around the world. As Gartner explains, IOCS “brings the world’s technology leaders together to hear top trends, find objective answers, and explore topic coverage in addition to best practices. Gain the insights and guidance to create an effective pathway to the future and network with your peers.”
The two key pillars of building reliable applications are: testing and monitoring. With testing, you can verify that each pull request works before it’s merged and deployed to production. Just testing isn’t enough, though. You also need to make sure that the application continues to work on production. Database rollovers, third-party outages, and unexpected spikes in traffic can all cause issues that need to be detected.
Cloud-based database providers often provide great observability out of the box. But, what if you’re developing a tricky feature locally and need more details about what your local Clickhouse is doing? There are many options, but if you’re a numbers and graphs person like me, you’ll want to be able to view the inner workings of Clickhouse in something like Grafana.
This is the ninth part of our 12-day Advent of Monitoring series. In this series, Checkly's engineers will share practical monitoring tips from their own experience. As a Checkly user, you’ve always had access to our two core check types: API and browser checks. API Checks are much cheaper, and therefore only run a curl-like request against the endpoint of your choice.
If you have large(r) customers, there is a point where they ask you for service-level agreements, or short SLAs. These are customer contracts defining different aspects of your service and what you guarantee for them. One common agreement is around availability, or, colloquially speaking, uptime. Your contract might state, and I am not a lawyer, that you guarantee that your service (or core parts of it) is available 99.99% of the time of a given period, mostly per month, quarter, or year.