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OpenSLO Specification Moves to Version 1.0

Nobl9 announced that, together with core contributors including some of the world's most renowned DevOps and Service Level Objective (SLO) experts, the community has released OpenSLO 1.0.

An open source project under the Apache 2 (APLv2) license, OpenSLO is the industry-standard SLO specification, designed to make SLOs accessible to modern developer Git workflow, and providing a common interface for widespread integration with the full ecosystem of cloud infrastructure, application monitoring and performance tooling.

“We put OpenSLO out there last year to spark a conversation, and it quickly turned into a de facto standard for describing SLOs-as-code,” said Brian Singer, co-founder and Chief Product Officer at Nobl9. “Open standards with proprietary implementations ensure end-users can feel confident their investment won’t lock them into a specific vendor. This is critical for enterprises adopting modern observability and reliability practices today.”

In the past year, there have been hundreds of contributions to OpenSLO to ensure enterprises can easily adopt and improve business operations with SLOs.

New functionality includes:

- A new object kind, DataSource, to allow for easier reuse of connection details and make creating SLOs easier and less verbose;

- Divided the SLO and SLI into separate objects to allow for better flexibility when moving between metric sources;

- Three new types of alerting: AlertCondition, AlertPolicy and AlertNotifcationTarget providing greater reuse and flexibility;

- More options to handle today’s ever changing environments like `alertWhenBreaching`, `alertWhenResolved` and `alertWhenNoData’; and,

- Nobl9 is also releasing an OpenSLO to Nobl9 converter. Customers leveraging OpenSLO can easily convert their OpenSLO YAML into Nobl9 YAML which they can then directly import into Nobl9 using sloctl.

Nobl9 launched OpenSLO last year and is a regular contributor to the open source project. In addition to direct contributions to the OpenSLO specification, Sumo Logic has contributed a new sub-project into OpenSLO called slogen. This open source tool takes OpenSLO-formatted YAML files to automate infrastructure configuration.

"Without a structured approach, the transition from classic monitoring to the SLO-driven methodology for Reliability Management, organizations struggle to reach maximum potential", said Christian Beedgen, CTO, Sumo Logic. “We’ve been able to infuse our platform with SLO capabilities by automating our configuration using OpenSLO via slogen, which today is now part of OpenSLO itself.”

The OpenSLO team invites the broader DevOps industry to participate in the evolution of this common reliability specification through integrations and features contributions, and from these classes of contributors in particular:

1- Application Lifecycle Management Vendors
2- Cloud Providers
3- Open Source Projects and Frameworks
4- Service Partners Consulting Enterprises on SRE and Agile

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OpenSLO Specification Moves to Version 1.0

Nobl9 announced that, together with core contributors including some of the world's most renowned DevOps and Service Level Objective (SLO) experts, the community has released OpenSLO 1.0.

An open source project under the Apache 2 (APLv2) license, OpenSLO is the industry-standard SLO specification, designed to make SLOs accessible to modern developer Git workflow, and providing a common interface for widespread integration with the full ecosystem of cloud infrastructure, application monitoring and performance tooling.

“We put OpenSLO out there last year to spark a conversation, and it quickly turned into a de facto standard for describing SLOs-as-code,” said Brian Singer, co-founder and Chief Product Officer at Nobl9. “Open standards with proprietary implementations ensure end-users can feel confident their investment won’t lock them into a specific vendor. This is critical for enterprises adopting modern observability and reliability practices today.”

In the past year, there have been hundreds of contributions to OpenSLO to ensure enterprises can easily adopt and improve business operations with SLOs.

New functionality includes:

- A new object kind, DataSource, to allow for easier reuse of connection details and make creating SLOs easier and less verbose;

- Divided the SLO and SLI into separate objects to allow for better flexibility when moving between metric sources;

- Three new types of alerting: AlertCondition, AlertPolicy and AlertNotifcationTarget providing greater reuse and flexibility;

- More options to handle today’s ever changing environments like `alertWhenBreaching`, `alertWhenResolved` and `alertWhenNoData’; and,

- Nobl9 is also releasing an OpenSLO to Nobl9 converter. Customers leveraging OpenSLO can easily convert their OpenSLO YAML into Nobl9 YAML which they can then directly import into Nobl9 using sloctl.

Nobl9 launched OpenSLO last year and is a regular contributor to the open source project. In addition to direct contributions to the OpenSLO specification, Sumo Logic has contributed a new sub-project into OpenSLO called slogen. This open source tool takes OpenSLO-formatted YAML files to automate infrastructure configuration.

"Without a structured approach, the transition from classic monitoring to the SLO-driven methodology for Reliability Management, organizations struggle to reach maximum potential", said Christian Beedgen, CTO, Sumo Logic. “We’ve been able to infuse our platform with SLO capabilities by automating our configuration using OpenSLO via slogen, which today is now part of OpenSLO itself.”

The OpenSLO team invites the broader DevOps industry to participate in the evolution of this common reliability specification through integrations and features contributions, and from these classes of contributors in particular:

1- Application Lifecycle Management Vendors
2- Cloud Providers
3- Open Source Projects and Frameworks
4- Service Partners Consulting Enterprises on SRE and Agile

The Latest

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

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 ...