Editorial illustration for Chronosphere Claims 85% Cost Cut and 10x Black Friday Performance vs. Datadog
Chronosphere Slashes Cloud Monitoring Costs with AI
Chronosphere pits AI against Datadog, touts 85% cost cut, 10× Black Friday load
Cloud monitoring startup Chronosphere is throwing down the gauntlet against industry giant Datadog, promising dramatic performance and cost improvements for enterprises wrestling with observability challenges. The company's bold claims center on using AI to radically transform how businesses track and manage their complex technology infrastructure.
Black Friday represents a brutal stress test for any digital platform, where sudden traffic spikes can cripple unprepared systems. But Chronosphere suggests its approach fundamentally changes that equation, offering reliability and efficiency that traditional monitoring tools can't match.
By reimagining data management at the ingestion level, the startup believes it can deliver major economic benefits. Its platform isn't just about watching systems, it's about intelligently controlling the massive data streams that can quickly balloon enterprise technology costs.
The implications could be significant for companies drowning in monitoring expenses and performance complexity. Chronosphere's approach hints at a potential shift in how organizations think about observability in an increasingly data-intensive technological landscape.
Astronomer achieved over 85% cost reduction by shaping data on ingest, and Affirm scaled their load 10x during a Black Friday event with no issues, highlighting the platform's reliability under extreme conditions." The cost argument matters because, as Paul Nashawaty, principal analyst at CUBE Research, noted when Chronosphere launched its Logs 2.0 product in June: "Organizations are drowning in telemetry data, with over 70% of observability spend going toward storing logs that are never queried." For CIOs fatigued by "AI-powered" announcements, Mao acknowledged skepticism is warranted. "The way to cut through it is to test whether the AI shortens incidents, reduces toil, and builds reusable knowledge in your own environment, not in a demo," he advised. He recommended CIOs evaluate three factors: transparency and control (does the system show its reasoning?), coverage of custom telemetry (can it handle non-standardized data?), and manual toil avoided (how many ad-hoc queries and tool-switches are eliminated?). Why Chronosphere partners with five vendors instead of building everything itself Alongside the AI troubleshooting announcement, Chronosphere revealed a new Partner Program integrating five specialized vendors to fill gaps in its platform: Arize for large language model monitoring, Embrace for real user monitoring, Polar Signals for continuous profiling, Checkly for synthetic monitoring, and Rootly for incident management.
Chronosphere's bold claims against Datadog spotlight a critical pain point in observability: runaway data costs. The platform's performance during Affirm's Black Friday test, scaling load tenfold without disruption, suggests serious technical chops.
Cost reduction isn't just a buzzword here. With analysts like Paul Nashawaty noting that organizations waste over 70% of observability spending on unqueried logs, Chronosphere's 85% cost-cutting approach could be major for tech teams.
The real-world validation from companies like Astronomer and Affirm adds weight to the platform's promises. By focusing on data shaping at ingest, Chronosphere seems to have cracked a persistent enterprise challenge: managing massive telemetry without breaking the bank.
Still, the competitive landscape remains complex. While these initial results are impressive, enterprises will likely want deeper proof points before wholesale migration. But for now, Chronosphere has certainly grabbed the observability market's attention with a provocative technical and economic argument.
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Common Questions Answered
How did Chronosphere help Astronomer reduce cloud monitoring costs?
Chronosphere enabled Astronomer to achieve over 85% cost reduction by implementing data shaping techniques during data ingest. This approach allows organizations to dramatically cut observability expenses by more efficiently managing and processing telemetry data.
What performance benchmark did Affirm achieve using Chronosphere during Black Friday?
Affirm successfully scaled their load 10x during the Black Friday event without experiencing any system disruptions using Chronosphere's monitoring platform. This demonstrates the platform's robust reliability and ability to handle extreme traffic and performance conditions.
Why are organizations struggling with observability spending according to analysts?
According to Paul Nashawaty from CUBE Research, organizations are currently wasting over 70% of their observability spend on storing logs that are never actually queried. This inefficient data management represents a significant economic challenge for enterprises managing complex technology infrastructure.