How Teamwork.com eliminated logging chaos, reduced MTTR from days to hours and freed up their engineering team with Bronto

Teamwork.com transformed their fragmented logging infrastructure, spanning 5-8 different tools across multiple AWS regions, into a unified, cost-effective solution with Bronto. This consolidation delivered immediate cost savings while enabling capabilities such as 365-day retention, sub-second searches across terabytes of data, and AI-powered insights that fundamentally changed how their teams work. The result was faster MTTR and engineering teams that could spend more time on high value work such as product development rather than managing internal logging infrastructure. 
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Business context

Teamwork.com is the AI-powered project management and resource management platform serving over 20k companies worldwide. Their platform includes Teamwork Projects, Desk, Chat, Spaces, and CRM, deployed across staging, US, and EU AWS regions. This distributed architecture generates massive log volumes, but their fragmented logging ecosystem was holding them back.

With engineering teams distributed globally and a growing cloud-native development environment, Teamwork.com needed complete visibility into their systems. Instead, their SysOps team was constantly fighting a battle against cost, complexity, and coverage limitations.
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Before: An operational burden 

In common with many organizations that have enjoyed rapid growth, Teamwork.com's logging infrastructure was a disparate set of solutions, each solving part of the problem while creating new ones:

• Self-hosted Graylog (multiple clusters across regions) for application logs
• AWS CloudWatch 
• AWS CloudTrail 
• ClickHouse + Superset for audit logs (implemented to escape CloudWatch costs)
• S3 buckets for traffic logs with painful Athena queries
• Prometheus for metrics that should have been logs

In addition there were significant AWS infrastructure costs to support these solutions, not counting the team’s productivity which was also being negatively impacted. Impacts on the team included: 

• SysOps burden: Constant maintenance of Graylog, Elasticsearch indices, and Fluentd agents.
• Developer frustration: "Where are my logs?" became a daily refrain. 
• Delayed resolution & blindspots: Missing data meant longer MTTR – not having ready access to the right data had a negative impact on the ability to resolve issues quickly.
• Architectural constraints: Teams avoided comprehensive logging, limiting observability

The Bronto Solution: From Chaos to Clarity

Bronto replaced Teamwork.com's entire collection of logging solutions with a single, unified platform that "just works":

• All logs in one place: Application, infrastructure, audit, CDN, streaming—everything
• Any format accepted: No more parsing rules, regex patterns, or index templates
• Zero maintenance: Fully managed SaaS eliminated operational overhead
• Multi-region support: Separate environments for staging, US, and EU with centralized visibility
• 12 months of hot data: negates the need to use Athena on archived S3 buckets - with the added benefit of giving wider access to this data, for example to customer support teams, and not only those engineers who can program Athena queries (and have access to the relevant AWS account). 
• Full logging coverage: no longer limited by cost or scale constraints‍
• Faster MTTR: The combination of more data, in one place, with faster search and better UX has lead to consistent MTTR efficiencies - issues that previously could have taken days to resolve are now handled in hours.Combined with proactive capabilities such as Brontoscope and statement ID support has allowed Teamwork.com to adopt a proactive rather than reactive approach to issue resolution.
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Total cost of ownership

Bronto proved to be 42% cheaper than running their previous collection of home-grown solutions, based solely on the cost of software and services. In fact, when Teamwork.com went out to the market to compare alternatives, they found that alternative SAAS solutions were up to 10X more expensive than Bronto with only 30 days retention (so it came as no surprise that they had opted to roll their own solution prior to Bronto).

The resources required to maintain their mix of disparate logging systems was also drastically reduced as follows:

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In summary, the total saving was 42% on software and services and freeing up the time of 2.2. FTEs to work on other projects. 
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New capabilities unlocked

An order of magnitude increase in retention period opened up new analytical use cases. Teamwork can now identify performance degradation patterns that have developed over months, trace customer issues back to their true origins, and base capacity planning on  historical data. Compliance audits that once required complex archive retrieval became simple searches.

When incidents struck, BrontoScope,  Bronto’s AI powered error investigator,surfaced root causes in seconds by analyzing millions of logs. Bronto helped to identify anomalies before they became incidents.

Bronto’s Usage Explorer gave control back to the SRE team.  Team and service level visibility into log volumes has been a game changer in understanding what logs are most valuable and most searched - it can also highlight logs that might be of high volume but low value. It also enables them to see what teams were responsible for spikes in log volumes, and using Bronto’s usage notifications, those responsible could be notified immediately. In one instance debug logs were accidentally turned on in production, and the team were notified right away preventing a high sustained increase in log volumes that would be of no value. 

The impact has rippled far beyond the engineering team. With all logs centralized, engineers created curated dashboards and saved views that less ops-familiar staff could actually use. Customer Support could investigate issues themselves using documented workflows instead of filing tickets and waiting for SysOps availability. Product managers accessed performance metrics through purpose-built dashboards without needing to understand complex queries. The time from customer complaint to insight dropped from hours or days to minutes, while engineering teams reclaimed countless hours previously spent on routine log retrieval and formatting requests.

This self-service model has significantly improved response time leading to better customer experience and reduction in low value manual effort. Now, with centralized logging and repeatable workflows, any team can follow standard procedures to get the insights they needed.