Lumigo Reviews

1. Rony

   over 5 years ago
   Just works out of the box.

   Before using Lumigo I worked with clients on all sorts of hacks to debug Serverless Apps. This involved cluttering the code base with logs and deciphering the output on CloudWatch. A fellow consultant told us about his success with Lumigo. We decided to give it a go. Within minutes, our customers started to enjoy meaningful, actionable insights. All our clients now probably enjoy a reduction of about 60 percent in our time-to-response has been cut by about 60 percent.

   🏁 Competitors: AWS X-Ray, Epsagon
2. Efraim MK

   almost 6 years ago
   Reduces the clutter when debugging Serverless applications

   I've been using Lumigo in the past year. It's been helping me find underline issues that are much harder to find compared to cloudwatch, it puts everything in a unified view and reduces the need to move between a list of logs in CloudWatch. I like the alerts that come out of the box and especially the integration with external tools, noo need for me to write any Lambda to interact with my Slack channel.

   🏁 Competitors: NewRelic, AWS X-Ray, Amazon CloudWatch

   👍 Pros:    Instant alerts|Easy to use|Easy log correlation

   👎 Cons:    Missing cli
3. Daniel Limon

   · CEO at TalkMeUp · almost 6 years ago
   APM + dist-tracing for serverless

   Best onboarding of an APM I've seen. No code changes and literally 5 clicks. Really helps the team spot production glitches and understand root cause immediately.

   I love the idea of presenting distributed system flow via visual maps !

   🏁 Competitors: Datadog, AWS X-Ray, NewRelic, Amazon CloudWatch, AppDynamics

   👍 Pros:    Seamless onboarding|Pre-configured serverless alerts|100% automated distributed tracing

   👎 Cons:    Does not support on premise servers

Scikit-learn Reviews

Lumigo mentions (14)

• Tracing On Kubernetes

  You can do so at this link: https://lumigo.io/. - Source: dev.to / over 2 years ago

• The biggest problem with EventBridge Scheduler and how to fix it

  Luckily, we just need to make sure the target Lambda function (for the schedule) receives the name of the schedule as part of its invocation event. Because the onSuccess function would receive this as requestPayload when it’s invoked by the Lambda service, as you can see from the trace collected in Lumigo:. - Source: dev.to / over 3 years ago

• The Risks of Moving Too Quickly with Serverless Development

  No Indicators of Success - As much as we'd all like it, observability tools don't automatically track your business metrics. You can add APM vendors like BaseLime, Lumigo, and DataDog to your account, but unless you intentionally add meaningful metrics to track your KPIs, you're left in the dark. Metrics tend to fall by the wayside in many scenarios where speed is the primary objective. No business metrics mean... - Source: dev.to / over 3 years ago

• Serverless takeaways

  Lumigo: Lumigo is similar to Datadog, but the main different is that lumigo focuses on traceability. The more incredible feature it is the graphs and the following to the transaction to the time of live. - Source: dev.to / over 3 years ago

• How to see the event that triggered a lambda?

  We’re using https://lumigo.io/ to trace our lambda functions and it’s a great deal in terms of what you’re paying and what you’re getting. Source: over 3 years ago

Scikit-learn mentions (40)

• Detecting Ingress Tool Transfer (T1105) with Python

  Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / about 2 months ago

• Best AI Cybersecurity Training for Security Teams: How to Pick

  Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / about 2 months ago

• Where to Get Hands-On AI Training for Cybersecurity Professionals

  Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 2 months ago

• How Anomaly Detection Actually Works in Security Operations

  Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 3 months ago

• Building a Personalized Meal Recommendation System

  In practice, you’ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 5 months ago