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SRE & Chaos Engineering


SRE and Chaos Engineering - the DOU Edge

The core tenets on which SRE works are as follows

Observability

Observability

In order to conduct experiments, one must be able to have deep introspection into the functionalities of the system.

Experimentation

Experimentation

Tightly define scope, time, and duration of experiments. Choose experiments where the risk/reward ratio is in your favor.

Reporting

Reporting

Chaos Engineers should do deep dives into codebases to determine sources of problems and work with engineers to fix problems and increase reliability.

Culture

Culture

Chaos engineering, like DevOps, is a cultural paradigm shift that provides incentives for engineers to design systems with reliability in mind.

Scale SRE practice in the enterprise

While it is common practice for System Admins to move into DevOps functions, enterprises still commit less Software Engineers for SRE teams. At DoU, our software engineers take on your hardest challenges, allowing your software teams to focus on their core areas and strengths.

For Observability, our specialized and expert SRE runs through the code/work with the software engineering teams to instrument the necessary metrics to monitor and emit. The team will also help write the custom dashboards for business or help write the observability platform.

Our key SRE delivery principles

01.

Mitigating Risks

02.

SLA Commitments

03.

Monitoring /Alerts

04.

Testing Automation

05.

Release Engineering

Reliability is key

DigitalOnUs is proud of enhancing the delivery standards to the next level of Site Reliability Engineering: Chaos Engineering.

Chaos Engineering brings in a massive paradigm shift with the design focus shifting to reliability as the key quotient, in comparison to systems that merely perform routine tasks.

Chaos Engineering increases reliability and uptime by surgically attacking the infrastructure to detect weak spots, thereby increasing resilience to service degradation. 

This is a notch higher than the conventional approach of typical Incident Response – Prevention lifecycle. Experiments are run, data is collected, and fixes are made. Instead of hoping that disaster recovery and failover work as expected, Chaos Engineering actively tests assumptions, clarifying what works and what does not, during outages.