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Cribl Announces Strategic Partnership with Elastic

Cribl announced a new strategic partnership with Elastic, the company behind Elasticsearch®, to provide customers with greater data flexibility, delivering enhanced data visibility, improved SIEM capabilities, and simplified migrations to Elastic Cloud.

The new partnership brings a deeper integration between the full Cribl suite of products and Elastic Security and Observability, enabling customers to more efficiently manage and operationalize their data. Additional Cribl Packs will be available to provide customers with out-of-the-box content that maps common log types to Elastic Common Schema (ECS), and in-product tiles will also be available alongside other pre-built integrations.

Cribl and Elastic together give customers a streamlined data management experience, with capabilities including:

- Enhanced data visibility with the power of Cribl’s pre-processing capabilities and Elastic’s real-time AI search analytics solutions for Observability, Security and Search, to tap into clear and concise data insights.

- Improved SIEM capabilities to enhance and accelerate incident response with streamlined data processing tools.

- Simplified migrations for cloud deployments, on-prem to cloud migrations, and SIEM migrations.

Additional customer benefits include enhancing Elastic’s search analytics capabilities with optimized data input, ensuring data meets regulatory standards throughout its lifecycle, and lowering operational costs through more efficient data processing.

“Getting the right data into the right tools, and doing that efficiently, is at the core of what we do for our customers. This new partnership with Elastic brings stronger interoperability between our product suites and enables customers to do more with their data,” said Zac Kilpatrick, Vice President of Global Channels & Alliances at Cribl. “Cribl enhances on-prem and cloud migration processes to Elastic Security and Observability. By helping customers transition from existing onboarding systems, we improve the management and control of enterprise logging and security pipelines. There’s massive value here for our customers, and we’re excited to work together to help customers realize the full power of their data.”

“Customers need visibility into their security and observability logging pipelines. Combining the unified Security and Observability capabilities of Elastic with Cribl’s data ingest, transformation, and routing features offered by Cribl brings a whole new level of flexibility to our clients — making it easier than ever to integrate and manage existing enterprise logging pipelines. Cribl’s use of the Elastic Common Schema will provide our customers with industry-leading flexibility to ingest, normalize, and manage the largest and most complicated security and observability pipelines,” said Laurent Mechain, Vice President of Strategic Alliances at Elastic.

In partnership with Cribl, Elastic is enhancing the OpenTelemetry (OTel) data integration process. This joint solution streamlines the transfer of OTel data into Elastic and builds on Elastic’s contribution of ECS to the OTel project earlier this year, which enables a unified specification for security and observability data within the OTel Semantic Conventions framework. The collaboration between Elastic and Cribl marks a significant advancement in the efficient and coherent management of security and observability data.

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Cribl Announces Strategic Partnership with Elastic

Cribl announced a new strategic partnership with Elastic, the company behind Elasticsearch®, to provide customers with greater data flexibility, delivering enhanced data visibility, improved SIEM capabilities, and simplified migrations to Elastic Cloud.

The new partnership brings a deeper integration between the full Cribl suite of products and Elastic Security and Observability, enabling customers to more efficiently manage and operationalize their data. Additional Cribl Packs will be available to provide customers with out-of-the-box content that maps common log types to Elastic Common Schema (ECS), and in-product tiles will also be available alongside other pre-built integrations.

Cribl and Elastic together give customers a streamlined data management experience, with capabilities including:

- Enhanced data visibility with the power of Cribl’s pre-processing capabilities and Elastic’s real-time AI search analytics solutions for Observability, Security and Search, to tap into clear and concise data insights.

- Improved SIEM capabilities to enhance and accelerate incident response with streamlined data processing tools.

- Simplified migrations for cloud deployments, on-prem to cloud migrations, and SIEM migrations.

Additional customer benefits include enhancing Elastic’s search analytics capabilities with optimized data input, ensuring data meets regulatory standards throughout its lifecycle, and lowering operational costs through more efficient data processing.

“Getting the right data into the right tools, and doing that efficiently, is at the core of what we do for our customers. This new partnership with Elastic brings stronger interoperability between our product suites and enables customers to do more with their data,” said Zac Kilpatrick, Vice President of Global Channels & Alliances at Cribl. “Cribl enhances on-prem and cloud migration processes to Elastic Security and Observability. By helping customers transition from existing onboarding systems, we improve the management and control of enterprise logging and security pipelines. There’s massive value here for our customers, and we’re excited to work together to help customers realize the full power of their data.”

“Customers need visibility into their security and observability logging pipelines. Combining the unified Security and Observability capabilities of Elastic with Cribl’s data ingest, transformation, and routing features offered by Cribl brings a whole new level of flexibility to our clients — making it easier than ever to integrate and manage existing enterprise logging pipelines. Cribl’s use of the Elastic Common Schema will provide our customers with industry-leading flexibility to ingest, normalize, and manage the largest and most complicated security and observability pipelines,” said Laurent Mechain, Vice President of Strategic Alliances at Elastic.

In partnership with Cribl, Elastic is enhancing the OpenTelemetry (OTel) data integration process. This joint solution streamlines the transfer of OTel data into Elastic and builds on Elastic’s contribution of ECS to the OTel project earlier this year, which enables a unified specification for security and observability data within the OTel Semantic Conventions framework. The collaboration between Elastic and Cribl marks a significant advancement in the efficient and coherent management of security and observability data.

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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 ...