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Site Reliability Engineering (SRE) is the Force Multiplier of Digital Experiences

Colin Fallwell
Sumo Logic

The pandemic spurred a wave of digital services because they allowed companies to stay competitive in the digital transformation. This trend, in turn, caused companies to adopt site reliability engineering (SRE) to keep up with the customer demand for digital experiences.

DevOps Institute recently published the Global SRE Pulse 2022 highlighting the growing adoption of SRE as a central operating model to deliver digital services and applications.


Even with over 62% of respondents saying their organizations are leveraging SRE within their company today, the survey shows that many organizations are at different stages within SRE adoption. Only 1% of respondents report that they tried SRE but that it did not work for their company.

SRE is now an essential engineering practice for enterprises seeking to accelerate digital transformations to digital-first brands. So how can companies empower SREs and adopt the model across their entire IT organizations to improve digital experiences and ultimately the business? It first starts with addressing the workforce gap and then breaking down team silos.

Closing the Skills Gap

The biggest challenge when adopting SRE is finding those with the right skills to make SRE to work properly — with 85% of respondents citing the lack of staff with necessary skills as their biggest challenge.

Leaders can address skill gaps by training talent and promoting within the organization. It's important to not only look at the technical skills but also at a candidate's ability to see and advocate for the relationship between engineering and business.

It's also essential to implement automation solutions to reduce the manual work of solving priority alerts. It's not just a matter of implementing technology though. Teams must also update processes to ensure the technology is used by everyone, including those who resist AIOps and automation.

The survey found that some teams are implementing intelligent automation everywhere to ensure the reliability and continuous operation of systems. Specifically, 29% of respondents said they are currently leveraging observability tools and techniques.

One method of advancing automation is through chaos engineering and intentionally destroying and rebuilding environments to improve both hygiene and confidence. However, 43% of survey respondents said they're not applying chaos engineering at all, so there is significant opportunity for those willing to learn the skills.

SRE Best Practices Can Unify Teams

Siloed teams is another common challenge for organizations. Communication and dependencies delay responses and innovation. SREs can bridge the gap between IT and developers if leaders first implement these SRE best practices across teams.

Track and manage toil. Toil is work that is manual, repetitive, automatable, tactical, or devoid of enduring value, and it scales linearly as a service grows. In the survey, 66% of respondents said they measure toil in some or several teams, and 11% indicated they track toil everywhere. By measuring toil, SREs can proactively reduce its effects across teams to improve reliability.

Provide ongoing support. Organizations also report implementing SRE best practices, including these across all teams:

- Adopting observability and monitoring tools (29%)
- Supporting essential job certifications (27%)
- Practicing a no blame philosophy (36%)

The two most widely adopted practices to at least some extent were practicing no blame (92%) and retrospectives or post-mortems (95%). The philosophy of learning from failure is what drives SRE success in many organizations.

Looking into the Future of SRE

Overall, the level of maturity revealed by the Global SRE Pulse survey indicates that many organizations are invested in improving SRE and making it part of their processes and cultures.

With 37% of organizations reporting that they have centralized SRE teams, it appears the practices and topologies are evolving. But the foundation for SRE is on solid ground and business leaders can expect SRE to remain a fixture in the industry. Beyond that, SRE also has the opportunity to be a unifying force between IT and business departments. By partnering with business and development teams, SRE will have the ability to influence and improve business outcomes.

Colin Fallwell is Field CTO of Sumo Logic

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

Site Reliability Engineering (SRE) is the Force Multiplier of Digital Experiences

Colin Fallwell
Sumo Logic

The pandemic spurred a wave of digital services because they allowed companies to stay competitive in the digital transformation. This trend, in turn, caused companies to adopt site reliability engineering (SRE) to keep up with the customer demand for digital experiences.

DevOps Institute recently published the Global SRE Pulse 2022 highlighting the growing adoption of SRE as a central operating model to deliver digital services and applications.


Even with over 62% of respondents saying their organizations are leveraging SRE within their company today, the survey shows that many organizations are at different stages within SRE adoption. Only 1% of respondents report that they tried SRE but that it did not work for their company.

SRE is now an essential engineering practice for enterprises seeking to accelerate digital transformations to digital-first brands. So how can companies empower SREs and adopt the model across their entire IT organizations to improve digital experiences and ultimately the business? It first starts with addressing the workforce gap and then breaking down team silos.

Closing the Skills Gap

The biggest challenge when adopting SRE is finding those with the right skills to make SRE to work properly — with 85% of respondents citing the lack of staff with necessary skills as their biggest challenge.

Leaders can address skill gaps by training talent and promoting within the organization. It's important to not only look at the technical skills but also at a candidate's ability to see and advocate for the relationship between engineering and business.

It's also essential to implement automation solutions to reduce the manual work of solving priority alerts. It's not just a matter of implementing technology though. Teams must also update processes to ensure the technology is used by everyone, including those who resist AIOps and automation.

The survey found that some teams are implementing intelligent automation everywhere to ensure the reliability and continuous operation of systems. Specifically, 29% of respondents said they are currently leveraging observability tools and techniques.

One method of advancing automation is through chaos engineering and intentionally destroying and rebuilding environments to improve both hygiene and confidence. However, 43% of survey respondents said they're not applying chaos engineering at all, so there is significant opportunity for those willing to learn the skills.

SRE Best Practices Can Unify Teams

Siloed teams is another common challenge for organizations. Communication and dependencies delay responses and innovation. SREs can bridge the gap between IT and developers if leaders first implement these SRE best practices across teams.

Track and manage toil. Toil is work that is manual, repetitive, automatable, tactical, or devoid of enduring value, and it scales linearly as a service grows. In the survey, 66% of respondents said they measure toil in some or several teams, and 11% indicated they track toil everywhere. By measuring toil, SREs can proactively reduce its effects across teams to improve reliability.

Provide ongoing support. Organizations also report implementing SRE best practices, including these across all teams:

- Adopting observability and monitoring tools (29%)
- Supporting essential job certifications (27%)
- Practicing a no blame philosophy (36%)

The two most widely adopted practices to at least some extent were practicing no blame (92%) and retrospectives or post-mortems (95%). The philosophy of learning from failure is what drives SRE success in many organizations.

Looking into the Future of SRE

Overall, the level of maturity revealed by the Global SRE Pulse survey indicates that many organizations are invested in improving SRE and making it part of their processes and cultures.

With 37% of organizations reporting that they have centralized SRE teams, it appears the practices and topologies are evolving. But the foundation for SRE is on solid ground and business leaders can expect SRE to remain a fixture in the industry. Beyond that, SRE also has the opportunity to be a unifying force between IT and business departments. By partnering with business and development teams, SRE will have the ability to influence and improve business outcomes.

Colin Fallwell is Field CTO of Sumo Logic

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...