determined
Sentry
determined | Sentry | |
---|---|---|
10 | 266 | |
2,868 | 36,957 | |
2.5% | 0.9% | |
9.9 | 10.0 | |
4 days ago | 6 days ago | |
Go | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
determined
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Open Source Advent Fun Wraps Up!
17. Determined AI | Github | tutorial
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ML Experiments Management with Git
Use Determined if you want a nice UI https://github.com/determined-ai/determined#readme
- Determined: Deep Learning Training Platform
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Queueing/Resource Management Solutions for Self Hosted Workstation?
I looked up and found [Determined Platform](determined.ai), tho it looks a very young project that I don't know if it's reliable enough.
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Ask HN: Who is hiring? (June 2022)
- Developer Support Engineer (~1/3 client facing, triaging feature requests and bug reports, etc; 2/3 debugging/troubleshooting)
We are developing enterprise grade artificial intelligence products/services for AI engineering teams and fortune 500 companies and need more software devs to fill the increasing demand.
Find out more at https://determined.ai/. If AI piques your curiosity or you want to interface with highly skilled engineers in the community, apply within (search "determined ai" at careers.hpe.com and drop me a message at asnell AT hpe PERIOD com).
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How to train large deep learning models as a startup
Check out Determined https://github.com/determined-ai/determined to help manage this kind of work at scale: Determined leverages Horovod under the hood, automatically manages cloud resources and can get you up on spot instances, T4's, etc. and will work on your local cluster as well. Gives you additional features like experiment management, scheduling, profiling, model registry, advanced hyperparameter tuning, etc.
Full disclosure: I'm a founder of the project.
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[D] managing compute for long running ML training jobs
These are some of the problems we are trying to solve with the Determined training platform. Determined can be run with or without k8s - the k8s version inherits some of the scheduling problems of k8s, but the non-k8s version uses a custom gang scheduler designed for large scale ML training. Determined offers a priority scheduler that allows smaller jobs to run while being able to schedule a large distributed job whenever you need, by setting a higher priority.
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Cerebras’ New Monster AI Chip Adds 1.4T Transistors
Ah I see - I think we're pretty much on the same page in terms of timetables. Although if you include TPU, I think it's fair to say that custom accelerators are already a moderate success.
Updated my profile. I've been working on DL training platforms and distributed training benchmarking for a bit so I've gotten a nice view into the GPU/TPU battle.
Shameless plug: you should check out the open-source training platform we are building, Determined[1]. One of the goals is to take our hard-earned expertise on training infrastructure and build a tool where people don't need to have that infrastructure expertise. We don't support TPUs, partially because a lack of demand/TPU availability, and partially because our PyTorch TPU experiments were so unimpressive.
[1] GH: https://github.com/determined-ai/determined, Slack: https://join.slack.com/t/determined-community/shared_invite/...
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[D] Software stack to replicate Azure ML / Google Auto ML on premise
Take a look at Determined https://github.com/determined-ai/determined
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AWS open source news and updates No.41
determined is an open-source deep learning training platform that makes building models fast and easy. This project provides a CloudFormation template to bootstrap you into AWS and then has a number of tutorials covering how to manage your data, train and then deploy inference endpoints. If you are looking to explore more open source machine learning projects, then check this one out.
Sentry
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Building a Production-Ready Web App with T3 Stack
First, sign up for a free account at https://sentry.io. Create a new project and make note of your DSN (Data Source Name).
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How to Handle N+1 Queries for Optimal Database Performance in Django?
Using APM tools like NewRelic, Sentry, Datadog, etc to monitor the performance of your application and while you're on it, they can help you identify N+1 queries.
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Next.js Error Monitoring with Sentry: Enhancing Your Application’s Reliability
However, ensuring the reliability and performance of your Next.js app is equally crucial. That’s where Sentry comes into play. Combined with Sentry, an industry-leading error monitoring platform, Next.js empowers developers to proactively identify and resolve issues that may arise in their applications. In this article, we’ll explore how to integrate Sentry into your Next.js project for effective error monitoring and performance optimization.
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4 facets of API monitoring you should implement
Sentry: Error monitoring for applications, including APIs. Also offers application performance monitoring (APM).
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It's 29 Delphi, I mean
Indeed, webapps are not immune to distribution problems. Wayward and invasive browser extensions are a clear threat, as are 3rd-party dependencies (and their dependencies) loaded at runtime. Which is why companies like https://sentry.io exist. I think the difference is that webapps are "distributable by default" and it takes real work to break this. Versus having local desktop apps which require work to distribute. A potent example of the power of defaults.
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We removed advertising cookies, here's what happened
Sentry produces nothing of value? You don't value an open source error tracking and performance monitoring platform? https://github.com/getsentry/sentry
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The Life and Death of Open Source Companies
> You invent something, and then immediately turn it into a cheap commodity by releasing it for free.
Exactly. A 71-line python script https://github.com/getsentry/sentry/commit/3c2e87573d3bd16f6... was groundbreaking when it came out and the fact that it springboarded into a startup is commendable.
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banner ads in spotify
sentry.io: 5
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Open Source alternatives to tools you Pay for
Sentry - Open Source Alternative For Error Tracking
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🤩 20 Awesome Tools For Your Web Dev Toolkit 🛠️
11. Sentry
What are some alternatives?
ColossalAI - Making large AI models cheaper, faster and more accessible
jaeger - CNCF Jaeger, a Distributed Tracing Platform
Dagger.jl - A framework for out-of-core and parallel execution
Loguru - Python logging made (stupidly) simple
aws-virtual-gpu-device-plugin - AWS virtual gpu device plugin provides capability to use smaller virtual gpus for your machine learning inference workloads
opentelemetry-specification - Specifications for OpenTelemetry
cfn-diagram - CLI tool to visualise CloudFormation/SAM/CDK stacks as visjs networks, draw.io or ascii-art diagrams.
skywalking - APM, Application Performance Monitoring System
goofys - a high-performance, POSIX-ish Amazon S3 file system written in Go
PostHog - 🦔 PostHog provides open-source product analytics, session recording, feature flagging and A/B testing that you can self-host.
alpa - Training and serving large-scale neural networks with auto parallelization.
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.