We realized that we need a way to automatically heal our platform from an operations perspective, and designed and built a workflow orchestration platform to provide these self-healing capabilities across our global network. We explore how this has helped us to reduce the impact on our customers due to operational issues, and the rich variety of similar problems it has empowered us to solve.

Highlights

Failure is an expected state in production systems, and no predictable failure of either software or hardware components should result in a negative experience for users. The exact failure mode may vary, but certain remediation steps must be taken after detection. A common example is when an error occurs on a server, rendering it unfit for production workloads, and requiring action to recover.

It can be tempting to rely on the expertise of world-class engineers to remediate these faults, but this would be manual, repetitive, unlikely to produce enduring value, and not scaling.

The commonality of lower-priority failures makes it obvious when the response required, as defined in runbooks, is “toilsome”. To reduce this toil, we had previously implemented a plethora of solutions to automate runbook actions such as manually-invoked shell scripts, cron jobs, and ad-hoc software services. These had grown organically over time and provided solutions on a case-by-case basis, which led to duplication of work, tight coupling, and lack of context awareness across the solutions.

A good solution would not allow only the SRE team to auto-remediate, it would empower the entire company. The key to adding self-healing capability was a generic interface for all teams to self-service and quickly remediate failures at various levels: machine, service, network, or dependencies.

Temporal is a durable execution platform which is useful to gracefully manage infrastructure failures such as network outages and transient failures in external service endpoints. This capability meant we only needed to build a way to schedule “workflow” tasks and have Temporal provide reliability guarantees.

After a workflow is validated in the staging environment, we can then do a full release to production. It seems obvious, but catching simple configuration errors before releasing has saved us many hours in development/change-related-task time.

Building a system that is maintained by several SRE teams has allowed us to iterate faster, and rapidly tackle long-standing problems. We have set ambitious goals regarding toil elimination and are on course to achieve them, which will allow us to scale faster by eliminating the human bottleneck.