Observability provider Coralogix nabs $200M investment. Coralogix Inc. today announced that it has raised $200 million in late-stage funding to enhance its observability platform. Advent, CPPIB and Greenfield led the Series F round with participation from Brighton Park Capital. TechCrunch reported that the investment values Coralogix at $1.6 billion. The cash infusion follows a year in which the company's revenue grew by more than 60%. Coralogix provides a cloud-based observability platform that ingests more than eight petabytes of data per day for more than 5,000 customers. The software collects telemetry from applications, cloud instances and a range of other technology assets. It turns the data into visualization that engineers can use to troubleshoot technical issues in their companies' infrastructure. Large datasets usually have to go through a process called indexing before processing can begin. The workflow produces an index, a collection of shortcuts that significantly speed up queries. However, the speedup only materializes once the index is assembled, which can take a significant amount of time. That means companies have to wait before they can start analyzing their telemetry. Coralogix's platform uses a technology called Streama to remove the need for indexing. Customers can start analyzing telemetry almost immediately after it's collected, which makes it possible to diagnose technical issues faster. Coralogix also skips several of the other steps usually involved in the data analysis workflow. Customers can query their telemetry using industry-standard syntaxes such SQL or the company's custom DataPrime language. According to Coralogix, the latter technology is faster because it's optimized for its observability platform's architecture. Additionally, DataPrime spares users the hassle of creating a schema, a file that defines the format of the data being processed. Retaining observability logs for an extended period of time can be costly. As a result, companies periodically delete their telemetry, which limits their visibility into historical technical incidents and long-term system behavior trends. Coralogix addresses the challenge by enabling users to keep telemetry in low-cost Amazon S3 buckets. Last year, the company rolled out an artificial intelligence assistant called Olly to its platform. The tool enables administrators to analyze technical issues using natural language prompts. Companies can also connect custom AI agents to the platform via an MCP server that Coralogix launched around the same time as Olly. "Engineers are no longer the only consumers of observability data," said co-founder and Chief Executive Officer Ariel Assaraf. "AI systems are becoming operational participants themselves. This funding allows us to accelerate that transition and build the intelligence layer required for the next generation of production operations." Coralogix reportedly also plans to build new cybersecurity features and grow its international presence. A message from John Furrier, co-founder of SiliconANGLE: Support its mission to keep content open and free by engaging with theCUBE community. Join theCUBE's Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities. * 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more * 11.4k+ theCUBE alumni - Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network. About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE, theCUBE Network, theCUBE Research, CUBE365, theCUBE AI and theCUBE SuperStudios - with flagship locations in Silicon Valley and the New York Stock Exchange - SiliconANGLE Media operates at the intersection of media, technology and AI. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Its new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.

Coralogix raises $200M to monitor AI agents gone rogue. Observability startup lands $1.6B valuation betting enterprises need guardrails for AI PUBLISHED: Wed, Jun 3, 2026, 1:57 PM UTC | UPDATED: Wed, Jun 3, 2026, 9:18 PM UTC Coralogix just closed a $200 million Series F at a $1.6 billion valuation, less than a year after its last fundraise. The timing isn't coincidental - the observability platform is racing to become the de facto monitoring layer for AI agents as enterprises scramble to deploy autonomous systems they don't fully trust yet. Led by Advent with participation from Canada Pension Plan Investment Board, the round signals investors believe someone needs to watch the watchers in the coming AI agent economy. Coralogix is making a calculated bet that the enterprise AI agent boom comes with a massive trust problem. The company just secured $200 million in Series F funding at a $1.6 billion valuation, with Advent leading and Canada Pension Plan Investment Board joining the round. What makes this raise notable isn't just the dollars - it's the speed. The company closed its previous round less than a year ago, signaling urgency around capturing the AI agent monitoring market before it consolidates. The observability space has traditionally focused on tracking application performance and infrastructure health. But Coralogix is pivoting hard toward a new problem - enterprises deploying AI agents that can make decisions, move money, and interact with customers without constant human oversight. According to sources familiar with the company's product roadmap, Coralogix has been quietly building tools to monitor AI agent behavior, detect hallucinations in real-time, track token costs spiraling out of control, and flag security breaches before agents go rogue. This isn't theoretical anxiety. Companies experimenting with AI agents report incidents where autonomous systems have approved unauthorized purchases, hallucinated fake customer data into CRM systems, and leaked proprietary information to external APIs. Traditional monitoring tools built for static applications can't catch these failure modes. Coralogix is betting that enterprises will pay premium prices for observability infrastructure purpose-built for AI's unique failure patterns. The funding comes as Datadog and New Relic scramble to add AI monitoring capabilities to their platforms. But Coralogix claims first-mover advantage with purpose-built agent observability rather than bolted-on features. The company's architecture ingests logs, metrics, and traces from AI systems, applies machine learning to detect anomalous agent behavior, and provides kill switches for autonomous workflows showing signs of instability. Advent's involvement signals institutional confidence that AI infrastructure spending will mirror cloud infrastructure's explosive growth curve. The private equity firm has deployed billions into enterprise software over the past decade, and sees observability as mission-critical for the coming wave of AI adoption. Canada Pension Plan Investment Board's participation adds strategic weight - pension funds don't chase hype cycles, they back infrastructure bets with decade-long horizons. The $1.6 billion valuation puts Coralogix in striking distance of competitors but still well below Datadog's public market cap north of $40 billion. The company will use the fresh capital to expand its AI agent monitoring product suite, hire engineers with machine learning expertise, and accelerate enterprise sales into Fortune 500 accounts already running pilot AI agent programs. Sources indicate Coralogix has signed deals with multiple financial services firms deploying AI agents for fraud detection and customer service automation. The raise also reflects investor anxiety about AI's deployment risks. As enterprises move from experimentation to production with autonomous systems, observability becomes table stakes. An AI agent that halluccinates in a demo is amusing. One that hallucinates in production with access to customer data and payment systems is a lawsuit waiting to happen. Coralogix is positioning itself as the insurance policy enterprises need before hitting deploy on AI agents with real authority. What's notable is the speed of this funding cycle. Less than a year between major rounds suggests either exceptional growth metrics or investor FOMO around AI infrastructure plays. Likely both. The observability market is consolidating rapidly, and companies without scale risk getting crushed between public market giants like Datadog and well-funded challengers. Coralogix needed capital velocity to match product velocity. The company faces stiff competition. Datadog already monitors infrastructure for most major enterprises and is extending those relationships into AI workloads. New Relic is pitching similar capabilities. Startups like Arize and WhyLabs focus specifically on ML observability. But Coralogix argues its full-stack approach - covering traditional infrastructure and AI layers simultaneously - gives customers unified visibility without stitching together point solutions. The $200 million bet on Coralogix reflects a broader market conviction - AI agents are coming whether enterprises feel ready or not, and someone needs to build the guardrails. Traditional observability tools were designed for predictable application behavior, not autonomous systems that can surprise even their creators. If Coralogix can establish itself as the standard monitoring layer before AI agents reach mainstream enterprise adoption, the $1.6 billion valuation might look conservative in hindsight. But the company's racing against well-funded competitors and a rapidly narrowing window to capture market share. The next 12 months will reveal whether this fast-follow funding round was prescient or premature. More Topics:

Coralogix secures $200M Series D to scale AI Observability platform. smart_toy AI-Assisted Analysis terminal // executive briefing tl;dr * [01] Coralogix raised $200 million in Series D funding to scale its AI-driven observability and security platform for high-growth enterprises. * [02] The platform unifies logs, metrics, traces, and security data to reduce monitoring complexity and lower data costs in cloud-native environments. * [03] Security leaders should evaluate unified observability platforms to bridge the visibility gap between DevOps and security operations teams. The convergence of observability and security operations. Coralogix recently announced a $200 million Series D funding round, bringing its total valuation to $1.6 billion, according to Coralogix. This significant capital injection highlights a growing trend in the cybersecurity industry: the blurring lines between DevOps observability and SOC visibility. As organizations migrate to complex, distributed microservices architectures, the volume of logs, metrics, and traces generated frequently exceeds the capacity of traditional SIEM platforms to ingest and analyze data cost-effectively. Traditional monitoring approaches often struggle with the sheer scale of cloud-native telemetry. The resulting data fragmentation makes it difficult for security teams to maintain a cohesive picture of their environment, leading to increased detection times and potential blind spots. Coralogix aims to solve this by providing a full-stack observability platform that unifies disparate data streams into a single, AI-enhanced interface. Technical analysis: scaling insights with Coralogix AI Observability platform features. At the core of the Coralogix offering is a unified platform designed to ingest high-velocity data and provide actionable intelligence without the prohibitive costs of indexing every single byte of data immediately. For security practitioners, this approach is vital. The ability to monitor for TTPs across hybrid cloud environments requires a platform that can distinguish between normal operational noise and the subtle indicators of an APT. One of the primary Coralogix AI observability platform features is its ability to perform stateful streaming analytics. Instead of waiting for data to be indexed in a database - a process that introduces significant latency - the platform analyzes data in transit. This allows for near real-time detection of threats like RCE attempts or Lateral Movement by identifying deviations from baseline behavior as they occur. By analyzing data before it is stored, organizations can trigger automated alerts at the edge, drastically reducing the window of opportunity for an attacker. Optimising security data processing with Coralogix. The high cost of data retention often forces SOC teams to make difficult decisions about which logs to keep and which to discard. This "data visibility gap" is frequently exploited by sophisticated attackers who hide their activities within unmonitored systems. By optimising security data processing with Coralogix, organizations can maintain a higher level of visibility without the linear cost increases associated with traditional logging solutions. This is achieved through a tiered storage and analysis model, where data is processed and alerted upon regardless of its eventual storage destination or indexing status. Detecting behavioral anomalies in cloud-native environments. In a modern cloud security context, static alert rules are often insufficient. Attackers frequently use legitimate credentials to perform actions that appear like normal administrative tasks. Therefore, detecting behavioral anomalies in cloud-native environments is a critical requirement for any observability-driven security strategy. Coralogix leverages machine learning to build dynamic baselines of "normal" behavior for every service, user, and API endpoint. When a microservice suddenly initiates a high volume of outbound connections or an administrative user accesses an unusual set of secrets, the platform can trigger an alert based on the statistical deviation, providing the necessary context for rapid incident response. Strategic implications for security leadership. The rise of "AI Observability" represents a fundamental shift from reactive monitoring to proactive resilience. For the modern SOC, the goal is no longer just to collect data, but to derive meaning from it at scale. As Coralogix expands its platform capabilities, the focus on unifying security and engineering data will likely lead to better collaboration between these traditionally siloed departments. Defenders should view this funding as a signal that the market is moving toward platforms that can handle the sheer scale of cloud-native telemetry. When evaluating observability tools, security leaders should prioritize those that offer native security integrations, automated anomaly detection, and a pricing model that encourages - rather than punishes - comprehensive data collection. This ensures that when a Zero-Day vulnerability is discovered, the organization has the historical and real-time data needed to perform a thorough impact analysis and remediation.