Alan Kao

💥 We recently announced Temporal Nexus - the feature that connects durable executions across team, namespace, region, and cloud boundaries. Nexus endpoints are API proxies for Nexus services that abstract Temporal primitives like Workflows for seamless integration and collaboration across teams 🤝 
 
Benefits for developers: - Familiar API programming model that supports both sync and async patterns for connecting durable executions using existing queue-based Workers. - Modular architecture that allows teams to independently develop, scale, and maintain parts of an application with clear API contracts backed by robust Nexus machinery. - Enhanced security, troubleshooting, and fault isolation that reduces the risk of misbehaving workers, since each team can run their workflows in separate namespaces. Use the Temporal SDK to add Nexus services to your existing workers with clean API contracts for others to use. Read more: http://temporal.io/nexus

111

2 Comments

📈 Exciting news for Pinecone and Datadog users! Our integration now fully supports Pinecone Serverless indexes, making it easier than ever to gain insights into your vector database’s health and improve performance. With this integration, you’ll have access to: • Detailed performance metrics on latency, usage, throughput, and more • Automatic alerts to help you stay on top of key metrics Explore the documentation to get started: https://lnkd.in/esAUaPVA Plus, for those using Prometheus, all metrics are accessible via HTTP service discovery, enabling seamless monitoring of indexes across all regions. Learn more about using Prometheus for Pinecone monitoring here: https://lnkd.in/ezYiyQzB #Pinecone #Datadog #Observability #Monitoring #Prometheus #Serverless #DataAnalytics

41

Here's what's new on Modal this month! 🐶 Datadog integration for application & audit logs ⚡️ Lower function latency 🎨 Refreshed app & function UI in the dashboard 🌎 Region selection & more client updates, read the full details:

23

🚀 Get ready for another Tech Deep Dive! Come learn how to integrate Apache Kafka with RisingWave from Emily L. on August 22! 💻✨ Emily will showcase how RisingWave handles data streams with Kafka topics, finishing with a live demo. 🎫 Don’t miss out—grab your spot here: https://lnkd.in/g6NJF3EP #risingwave #kafka #apachekafka #dataprocessing #streamprocessing

11

The shift from traditional ML to LLMs has pushed infrastructure requirements to new limits. At neptune.ai, we’re tackling these challenges by focusing on: → Scalable infrastructure, built to handle high-speed data ingestion and processing. → Real-time data display, adapting seamlessly to complex and large volumes. → Consistent UX quality, even under intense backend demands. — (link to the full interview in the comments) #generativeai #genai #llm

3

1 Comment

And we’re live. 🚀 Today, we’re thrilled to announce we’re launching out of stealth with $10.5 million in funding to build a unified dataops platform. When co-founders Benjamin Segal & Geva Segal started Matia, they wanted to solve a real problem they saw in the data and engineering world. They were managing and scaling large teams, and relying on disparate tools to move their data to Snowflake and back to their SaaS platforms, another tool to leverage their data lineage, and another one to monitor their data pipeline quality. Their teams were full of talented engineers, but they were spending most of their time piecing together their data stack and investigating anomalies, rather than focus on their core job. So they spoke to other data and engineering leaders about how they solved this problem. Everyone agreed it was an issue, but no one had the solution. And as more companies adopted AI strategies, the importance of an observability platform that natively monitored data before it was even ingested became even more important. So that’s where the idea of Matia was born: A unified dataops platform bridging together ingestion, reverse ETL, observability and catalog. 🧠 With pre-built connectors, data and AI teams can plug in seamlessly to the tools they use, and integrate with Databricks, Snowflake and even monitor transformations natively in dbt Labs. While it’s only the beginning of our journey, we’re grateful to have amazing customers like Ramp, Obligo, & HoneyBook onboard and already seeing incredible results, and backed by investors including Leaders Fund, Secret Chord Ventures, Cerca Partners & Caffeinated Capital. The best is yet to come. Follow our journey. Link in comments for more.

81

20 Comments

Why an ex-Coinbase Engineer chose SigNoz over Datadog 👇 Shiv Ansal is the co-founder and CTO of BANDS, an innovative product aimed at empowering musicians by providing them with an all-in-one toolkit to manage their careers. Learn why he chose SigNoz to be a trusted partner for observability:

10

ICYMI 📣 Here's the inside scoop from #theCUBE's coverage of #MongoDBlocal NYC. https://lnkd.in/gY4FeTRX 💡 Data is the driving force behind the AI surge. MongoDB's MAAP is empowering enterprise AI with seamless integrations, technical expertise, and robust architectures. 🌐 Strong partnerships with Microsoft, Google and Amazon Web Services (AWS) show MongoDB's commitment to adapting its ecosystem for developer-friendly features, as with Arc XP. 🗣️ “MongoDB is putting so much investment and innovation into the industry, including the MAAP initiative,” said David Vellante, theCUBE Research’s chief analyst. Get up to speed on how #MongoDB is redefining the AI landscape! #TechNews #CTOtrends #CloudComputing #DevOps #enterpriseAI #DataManagement

4

Congrats to the team at Rockset on their acquisition by OpenAI! 🚀 We’re excited to see how their tech and expertise will boost OpenAI’s real-time capabilities. Unfortunately, this means the Rockset commercial product will be discontinued. If you're a Rockset customer looking for alternatives, we'd love to help you. Seamlessly migrate your Rockset data to Imply Polaris, a fully managed, cloud-native analytics database built from #ApacheDruid. 🧙🏼‍♂️ https://lnkd.in/ejQqPbw2 #Rockset #OpenAI #ChatGPT #AI #LLM #realtimeanalytics #streamingdata #Apache

5

2 Comments

If you want to learn about systems that power gen AI (and how Codeium does this in a novel way)- this presentation from my man Kevin is a must watch!

7

1 Comment

Custom LLMs are starting to emerge for select workloads that require very high computational power and deep customization for particular use cases, such as Healthcare and FinServ. We're building a partnership with Ginkgo Bioworks to help them accelerate drug discovery and drive better patient outcomes. The models are huge -- trained on billions of proprietary Ginkgo protein sequences -- and Ginkgo is now making these models publicly available for researchers and developers via a programmer-friendly API. There's a nice article in Forbes out today which lifts the curtain a bit of what's going on and where we're headed. https://lnkd.in/gTUU45v5

11

Predictions for the future of LLMOps are varied.   But what is clear from speaking to Clemens Rawert, Co-Founder at Langfuse;   Is that users have become a lot more thoughtful and systematic as LLMs have matured.   And building golden datasets are going to be even more important for quality benchmarks.   Just 2 points of importance at Langfuse (YC W23), Take a look at the video to find out what else.... 💡

6

🐶 If you’re looking to get the most out of your Datadog environment check out our latest Fireside Chat between Senior Cloud Engineer Dan Roy and Senior Datadog Engineer Alex Glenn about Datadog Platform Optimization. Learn how RapDev can help you with log configuration, personalized integrations, and single-step #APM. Watch now - https://rap.dev/3AACKUm

17

Nothing beats the combined power of Trino and Iceberg 💪 Check out this episode of the data engineering podcast to learn about how Kevin Liu and the team at Stripe are utilizing these technologies to build some interesting features ⬇️ #trinodb #ApacheIceberg #Icehouse

7

Great post and guide from Nicholas White! Knowing what I know now, I would've invested more time in learning about large language models (LLM) and AI earlier in my career. But, it's never too late to start. Interested in learning about LLMs and generative AI? You can learn more here: https://lnkd.in/e8BqNFg9

3

Accelerating TiDB Adoption at Plaid: How Six Engineers Moved 41 services from Amazon Aurora MySQL to TiDB, powered by PingCAP in a year! https://lnkd.in/g-7Tdp_n

9

At Jellyfish, we’re dedicated to empowering engineering leaders by providing robust tools to measure and communicate the impact of their teams’ work. Today, we’re taking that one step further with the launch of the Jellyfish API. 🎉 The Jellyfish API gives you the flexibility to connect operational metrics, software deliverables, and engineering investment data to the tools and workflows that power your business. Whether it’s centralizing information or reducing context switching, the possibilities are endless. We tested out our brand new API with Amazon Web Services (AWS) Q Business in order to speed up API utilization, and provide on-demand insights that could be requested in various workflows outside the Jellyfish platform. Here's what we learned:  ✅ Guided API Exploration: Amazon Q helped us quickly identify the right API calls and outputs.   ✅ On-Demand Insights: We used Jellyfish data to answer key questions like team performance, project progress, and metrics — all in natural language.   ✅ Limitless Potential: From automating updates to integrating with tools like Slack, the Jellyfish API opens the door to a more seamless engineering workflow. We’re excited to see how our customers will innovate with this API. Got ideas or want to explore? Email us at api@jellyfish.co. Let’s build something amazing together!

41

4 Comments

Thanks to everyone who joined us for the Dagster+ launch! Dagster+ is an exciting redefinition of #dataorchestration aimed at: • reducing spend via cost #observability • eliminating error-prone point-solutions • enabling #data teams to operate autonomously Learn more about Dagster+ and get started for free here: https://bit.ly/3JnpZ0l

37