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p/digma-aiPreempt the issues your tests miss
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Ben Lang

Digma Preemptive Observability - Preempt performance and scaling issues in pre-production

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Digma is a Preemptive Observability product that identifies performance and scaling issues in pre-production environments and provides a code-level root cause and the severity of the issues, all done automatically and continuously.

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Ben Lang
Hunter
📌
Congrats team digma, awesome launch!
Roni Dover
Maker
WHAT IS DIGMA Digma's Preemptive Observability 👀 brings an innovative approach for using observability data to preempt issues before they manifest, instead of relying on alerts to fix them after the fact 🤦‍♂️. OBSERVABILITY IN THE AGE OF GENAI 🤖 AI code generation is revolutionizing software development, enabling teams to build faster than ever before. But with speed comes risk—without visibility into potential flaws, AI-generated code can introduce performance issues, scalability bottlenecks, and security vulnerabilities that only surface in production. Dealing with a continuous stream of production incidents drags down the team's velocity and creates constant friction for end users. PREEMPT VS POST MORTEM 🧟 Teams that aim to stop issues early and before they reach production, cannot rely on a postmortem approach using APMs. These tools are built to alert the team to issues and facilitate investigation once the problem already occurred. Digma switches to a preemptive approach. It analyzes the same data as APMs and identifies specific code issues using patterns, nipping them in the bud while still in pre-production. To close the loop, Digma provides AI fix suggestions. KEY FEATURES → Continuously identify code performance, scaling issues, query problems, and other issue types 🐞 → Cut resolution time by automatically root cause analyzing each issue as well as providing AI-driven fix suggestions ⚡️ → Prevent breaking changes by highlighting the affected areas and impacted components for each code change and Pull Request → Scaling up your application by identifying which areas of your codebase will scale seamlessly and which may create bottlenecks ⚖️ → Prioritizing technical debt 💰 by assessing existing issues i impact and criticality → Using OTEL-based observability with all supported programming languages and platforms. ☕️ → IDE and code integration: See issues, insights, and analytics within the code itself as well as metrics and traces 🔭 THE PREEMPTIVE OBSERVABILITY ANALYSIS (POA) ENGINE The Digma Preemptive Observability Analysis (POA) engine introduces an advanced approach to observability by proactively identifying potential issues before they materialize in production. It achieves this by analyzing observability tracing data, even when data volumes are low. Leveraging pattern matching and anomaly detection techniques, Digma’s algorithm extrapolates expected application performance metrics, enabling it to detect deviations or potential problems that have not yet impacted the application. In analyzing the tracing data, Digma pinpoints the issue to the specific responsible code and commits. We are super excited to bring Digma to more teams and see the kind of impact it makes on your development process. 🙏 Roni & Nir Digma co-founders https://digma.ai Try our live sandbox: https://sandbox.ui.prod.digma.sy...
Seunghwan
@roni_dover Looks nice! Congrats on launching digma
Alex Piliavsky
How is Digma different from other observability tools?
Nir Shafrir
Maker
@alex_digital3x Hey Alex, most observability tools are taking the post mortem approach which is monitoring production and alerting when there is already a problem, Digma is a preemptive observability tool which identify the same issues but much before they reach production, allowing the teams to fix them earlier. cheers
Roni Dover
Maker
@alex_digital3x Great question! APM tools are mostly focused on alerting and providing the data in post-mortem. Digma is unique in being preemptive - finding issues before they manifest in prodution
courtney glymph
Looks great, team. Regarding production, I’m curious about any potential performance impacts and resource consumption. Could you elaborate on that?
Roni Dover
Maker
Hey @courtney_glymph ! Digma uses your current observability datastream so will not incur any additional performance cost to your application!
Nahum Timerman
Do I need to make code changes for Digma to work?
Kyrylo Shmidt
@nahum_timerman No, Digma requires no code modifications or additional observability instrumentation. It works out of the box with your existing setup.
Roni Dover
Maker
@nahum_timerman awesome question - if you're already using observability there is no need to make any changes
Shaul Ben Maor
How does Digma alert teams to issues in pre-production?
Roni Dover
Maker
@shaul_ben_maor thank you for your question - Digma analyzes the observability data and provides teams with data on the stability of their release as well as alerts them to any escalations and critical issues.
Abhishek Ambad
Congrats on the launch team @Digma Preemptive Observability
Lee Sheinberg
Maker
Gheorghe Pisarenco
Can Digma help prepare my application for sudden scaling?
Gheorghe Pisarenco
@ionuiux, looking forward. Seems to be realy interesting.
Ankit Sharma
This sounds like a smart way to catch issues early! How does it integrate with existing workflows?
Shay Keren
Maker
@startupsharma You can integrate it with your CI pipeline using our API to either block builds or send notifications about issues in the code. Additionally, our web admin page provides a summary of all detected issues across different environments, making it easy to monitor and manage them
Jennifer Reid
Looks super interesting! What's the pricing model for a single developer vs. team?
Shay Keren
Maker
@jennifer_reid3 It’s free for individual developers! You can check our pricing details here: https://digma.ai/pricing/
Jennifer Reid
@shay_keren Thanks very much!
Sharon Shafran
Transformative product, I will highly recommend for any SW team out there to start using it ASAP
Yael Wagner
Kudos team Digma!
Valentyn Dudinov
Is there a discount for annual billing?
Nir Shafrir
Maker
Hi @valentyn_dudinov , in the pricing page https://digma.ai/pricing/, we mention that we only do annual billing.
Valentin Nalivayko
What happens if my team exceeds the user or endpoint limits in the Innovator Tier?
Lee Sheinberg
Maker
@valentin_nalivayko Hey Valentin, thanks for your comment::) You’ll need to upgrade to the Digma for Teams plan, which supports unlimited users and endpoints.
Celine Borsberry
Congratulations! Please can I ask how much it costs and if you have a pay as you go plan? Can you also elaborate on your enterprise plan?
Nir Shafrir
Maker
Hi @celine_borsberry1 , please check our pricing page https://digma.ai/pricing, there is a plan for a single team limited by 5 microservices and then for the enterprise plan, it is prices per the amount of microservices, so you can pay as you grow.
Eran Artzi
Looks interesting. No VS Code support?
Roni Dover
Maker
@eran_artzi1 Hey Eran we are no longer just IDE bound - you can use our web interface to see al of the info even if the IDE isn't supported
Eran Artzi
@roni_dover from the pricing page it seems that the web interface is only available on the paid tiers?
Roni Dover
Maker
@eran_artzi1 yes we have a standalone version that just installs to the IDE (IntelliJ) and is more toward experimentation but since we don't run any sophisticated data science on the local laptop using our central install provides the most capabitlies. We have a trial tier for that as well
Alexander Alkor
Looks so interesting for code development, will certainly add them to my list to try!
Edan Evantal
How does Digma alert teams to issues in pre-production?
Roni Dover
Maker
@evantal great question - Digma can alert to pre-production issues by identifying them in the pre-production observability
Roy Povarchik
Can it help with our performance testing environment?
Nir Shafrir
Maker
Hi @roypovar , yes it definitely can. in most performance testing environment engineers are correlating metrics from different version, trying to catch regressions, yet they have no means to identify the root cause of the regressions, which leads to hours or days of troubleshooting, while versions keep updating in production. Also, since it is all about manual defining and recording thresholds, they might not define a metric in a place that experience a regression, an issue that will eventually materialize in production. With Digma performance testing looks completely different: 1. Digma finds issue with no need to pre-define metrics/ thresholds. 2. Per every issue, an RCA is automatically given at the code level. 3. the performance testing environment doesn't have to mirror the production load, as Digma identifies issues by their patterns which doesn't change because of too much or too little load.
Amir Shevat
This is very exciting to see that you launched here. Super high value product💙