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Sumo Logic Debuts New Capabilities to Support Microservices Architecture

Sumo Logic announced new platform capabilities to make it easier to automate, manage and gain business insights from their microservices-based, modern application architectures that use containers, such as Docker, and orchestration software, like Kubernetes and Amazon EKS.

With these improvements, Sumo Logic is bringing together the power of contextual and telemetry insights across containers, orchestration and underlying application infrastructure for users to gain end-to-end, holistic visibility into their modern application architectures.

Sumo Logic’s new platform enhancements provide richer metadata support for instrumentation, analytics and cloud platforms, and to convert unstructured data to structured, time series data in real-time, means users will be able to extract more business value from their machine data faster to speed application improvement cycles, deliver better customer experiences and increase decision-making across the organization.

Sumo Logic is announcing three new key capabilities at DockerCon 2018 that deliver valuable operational and business insights for modern applications in the cloud.

- Reduce Downtime with Deeper Native Support for Kubernetes Anywhere. Sumo Logic’s native integrations and out of the box insights into Kubernetes and Docker already address a major blind spot for businesses adopting microservices and cloud in order to compete in today’s complex IT landscape. Sumo Logic now supports Kubernetes wherever it runs with native support for Amazon Elastic Container Service for Kubernetes (Amazon EKS) new managed service. Additionally, Sumo Logic has added support for performance metrics and metadata via the open source standard Prometheus used by the Kubernetes community. This allows customers to ingest metrics and metadata relevant to monitoring Kubernetes clusters, to quickly and proactively resolve customer issues and reduce downtime.

- Optimize Machine Data for Improved Analytics Performance. Unstructured machine data is not always optimized for the kind of real-time analytics customers need to inform business decisions. Now with Sumo Logic, customers can easily extract performance metrics and key performance indicators from unstructured logs, while still retaining those logs for root cause analysis. These metrics can then be used with the Sumo Logic time series engine, providing 10 to 100 times the analytics performance improvements over unstructured log data searches, as well as support long-term trending of metrics.

- Easily Extract Valuable Business Insights from Machine Data. Increasing the accessibility of essential machine data insights and mapping those to actionable, contextual business analytics for IT and non-core-IT users is critical. In addition to full metadata support for Kubernetes, as mentioned above, users can now convert their existing Graphite-formatted performance metrics into the metadata-rich, metrics 2.0 format supported by Sumo Logic, both in real-time and after ingestion. This allows customers to increase the usability and accessibility for their analytics users by allowing them to leverage business relevant tags, instead of relying only on obscure, technical tags. Sumo Logic has also unveiled custom tagging support for any log source.

“The world is moving from generic solutions to personalized ones that address very specific customer pain points, and this requires an agile and flexible platform built for the cloud,” said Bruno Kurtic, founding VP of Product and Strategy, Sumo Logic. “Legacy analytics tools have failed organizations because they can no longer deliver the visibility needed to support the investment customers are making in modern architectures at cloud scale. The new enhancements to Sumo Logic’s platform not only provide real-time access to machine data analytics as a service, but also make data easily accessible to everyone enabling organizations to leverage these insights to drive better experiences for their customers.”

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Sumo Logic Debuts New Capabilities to Support Microservices Architecture

Sumo Logic announced new platform capabilities to make it easier to automate, manage and gain business insights from their microservices-based, modern application architectures that use containers, such as Docker, and orchestration software, like Kubernetes and Amazon EKS.

With these improvements, Sumo Logic is bringing together the power of contextual and telemetry insights across containers, orchestration and underlying application infrastructure for users to gain end-to-end, holistic visibility into their modern application architectures.

Sumo Logic’s new platform enhancements provide richer metadata support for instrumentation, analytics and cloud platforms, and to convert unstructured data to structured, time series data in real-time, means users will be able to extract more business value from their machine data faster to speed application improvement cycles, deliver better customer experiences and increase decision-making across the organization.

Sumo Logic is announcing three new key capabilities at DockerCon 2018 that deliver valuable operational and business insights for modern applications in the cloud.

- Reduce Downtime with Deeper Native Support for Kubernetes Anywhere. Sumo Logic’s native integrations and out of the box insights into Kubernetes and Docker already address a major blind spot for businesses adopting microservices and cloud in order to compete in today’s complex IT landscape. Sumo Logic now supports Kubernetes wherever it runs with native support for Amazon Elastic Container Service for Kubernetes (Amazon EKS) new managed service. Additionally, Sumo Logic has added support for performance metrics and metadata via the open source standard Prometheus used by the Kubernetes community. This allows customers to ingest metrics and metadata relevant to monitoring Kubernetes clusters, to quickly and proactively resolve customer issues and reduce downtime.

- Optimize Machine Data for Improved Analytics Performance. Unstructured machine data is not always optimized for the kind of real-time analytics customers need to inform business decisions. Now with Sumo Logic, customers can easily extract performance metrics and key performance indicators from unstructured logs, while still retaining those logs for root cause analysis. These metrics can then be used with the Sumo Logic time series engine, providing 10 to 100 times the analytics performance improvements over unstructured log data searches, as well as support long-term trending of metrics.

- Easily Extract Valuable Business Insights from Machine Data. Increasing the accessibility of essential machine data insights and mapping those to actionable, contextual business analytics for IT and non-core-IT users is critical. In addition to full metadata support for Kubernetes, as mentioned above, users can now convert their existing Graphite-formatted performance metrics into the metadata-rich, metrics 2.0 format supported by Sumo Logic, both in real-time and after ingestion. This allows customers to increase the usability and accessibility for their analytics users by allowing them to leverage business relevant tags, instead of relying only on obscure, technical tags. Sumo Logic has also unveiled custom tagging support for any log source.

“The world is moving from generic solutions to personalized ones that address very specific customer pain points, and this requires an agile and flexible platform built for the cloud,” said Bruno Kurtic, founding VP of Product and Strategy, Sumo Logic. “Legacy analytics tools have failed organizations because they can no longer deliver the visibility needed to support the investment customers are making in modern architectures at cloud scale. The new enhancements to Sumo Logic’s platform not only provide real-time access to machine data analytics as a service, but also make data easily accessible to everyone enabling organizations to leverage these insights to drive better experiences for their customers.”

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
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