
Sumo Logic announced several innovationsmaking it easier for customers to stay competitive in today’s Intelligence Economy. The new enhancements to the company’s platform includes next-generation dashboarding visualization for faster data insights, a Data Enrichment for logs feature that gives users richer metadata for users to describe their log data streams in a more natural and intuitive way and Metric Transformation Rules for advanced control over their time series data.
The company also announced updates to its Global Intelligence Service and added new security out-of-the-box security applications to help security teams better prioritize their security incidents and accelerate response.
In addition, new integrations with Slack and MongoDB provide customers with expanded monitoring capabilities to help them audit and secure these popular enterprise technologies.
“Today, unstructured data created by digital services such as IoT, mobile apps, websites, and SaaS services is the primary source of signal for businesses. Without a way to consolidate these signals into a single, real-time view, companies remain stuck in an intelligence gap,” said Christian Beegen, co-founder and CTO, Sumo Logic. “The new capabilities and integrations we announced today provide our customers with the opportunity to close this gap by securing applications, introducing new services and improving customer experience.”
Sumo Logic’s cloud-native, Continuous Intelligence Platform enables three solutions for customers: Operational Intelligence, Security Intelligence and Global Intelligence. The new platform and solution improvements announced today span across all three areas to help customers leverage analytics and insights to build, run and secure their modern applications and cloud infrastructures.
Operational Intelligence innovations include:
- Next-Gen Dashboard Visualizations enable customers to have rich unified analytics across their metrics and logs data with detailed visual control for optimal monitoring and troubleshooting. Customers can now templatize their dashboards to rescope data on the fly, get interactive and data-dense visuals that help them isolate patterns quickly, and export dashboards to PDF or PNG for easy sharing via email or Slack.
- Data Enrichment for Logs gives customers the ability to describe their log data in a natural and intuitive way by mapping their mental model of how they think about logs to simple key value pairs. Sumo Logic has extended the already extensive metadata support of their metrics product to log data, including automatically capturing metadata from integrations - including the new Kubernetes solution. With this new feature customers can freely tag their logs with simple key-value pairs, helping them investigate and solve issues faster. Any Sumo Logic collector and log source will now support adding key-value pair fields. These fields can be used everywhere in Sumo Logic, from searching logs to securing access via RBAC.
- Metrics Transformation Rules helps users maximize the value of their time series data by giving them control of the granularity and retention of this data. With fine-control over the retention of their time series data, they can now keep high cardinality, high volume operations data for just a few days, while also aggregating the raw data into high-performance, Key Performance Indicators (KPIs) that can be cost-effectively stored for months.
The Security and Global Intelligence updates include:
- New updates to Global Intelligence Services (GIS) for Amazon GuardDuty provide customers a threat anomaly score based on the unusualness of their threat findings they can use to assess their security posture, prioritize responses, and generate a remediation plan. GIS for Amazon GuardDuty helps SecOps professionals cut through the clutter of security alerts and threats by giving them the ability to benchmark their GuardDuty findings against a baseline computed across the broader AWS user base in real time. In addition to the threat anomaly score, customers can leverage a rare events capability that detects threats that are not common in the broader AWS user community, but appear in the customer’s account, to further assist with threat detection and threat hunting.
- 30+ New and Updated Out-of-the-Box Security Applications that further help customers ingest, enrich, and visualize insight from critical elements of their defense. Sumo Logic has updated core applications such as Carbon Black, CrowdStrike, Okta, and Netskope as well as developed new integrations with Aqua, StackRox, and Twistlock that enhance the security of Kubernetes and the modern application stack. In addition, new applications to secure AWS, GCP and Azure extend Sumo Logic’s multi-cloud and hybrid security intelligence solution. With more than 200 total out-of-the-box applications, customers can integrate intelligence across a breadth of both security and operations use cases.
Sumo Logic unveiled integrations with new partners to roll out applications that further expand security and monitoring capabilities and increase users visibility into technologies being used at the heart of enterprises today. These new integrations include:
- Slack - The Sumo Logic App for Slack gives customers the ability to closely monitor external users, access patterns, member profiles, and audit all actions in one place. With this single-pane-of-glass view, users can quickly identify if and when critical data leaves the organization and correlate information across workspaces, channels, member and types (i.e. guest) to accelerate their security, audit incident investigation and threat hunting efforts.
- MongoDB Atlas - The Sumo Logic App for MongoDB Atlas gives customers comprehensive visibility into operations, health and security of their Atlas clusters. With this out-of-the-box solution, users can optimize the performance of an Atlas cluster by identifying slow and inefficient queries and monitor key database and system metrics to determine how to optimize your Atlas cluster resources. For security, users can monitor user logins and audit events, projects and organizational activity. In addition, they can also detect potential incoming threats and indicators of compromise via a built-in threat intelligence database.
The Latest
Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...
Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...
For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...
PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...
The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...
Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...
Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...
On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...
Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...
Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...