How to Get Logs from Docker Containers
Learn how to access, filter, and monitor Docker container logs, plus tips for structured logging, rotation, and production-ready setups.
Updates and recent posts about BigQuery.. Link
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@anjali shared a link, 11 months, 2 weeks ago
Customer Marketing Manager, Last9
Improve Consistency Across Signals with OTel Semantic Conventions
Correlate logs, metrics, and traces faster by using consistent field names and schemas with OpenTelemetry semantic conventions.
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@anjali shared a link, 11 months, 2 weeks ago
Customer Marketing Manager, Last9
How Replicas Work in Kubernetes
Understand how Kubernetes uses replicas to ensure your application stays available, handles traffic spikes, and recovers from pod failures automatically.
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@arshadmas shared a post, 11 months, 2 weeks ago
Product Marketer, manageengine
GCP monitoring: A comprehensive guide into maximizing cloud performance
Keeping mission-critical workloads healthy on Google Cloud Platform (GCP) isn’t optional—it’s your job. As organizations increasingly move to GCP for its elasticity and scalability, the complexity of managing cloud-native and hybrid environments grows. For ITOps and CloudOps professionals, the chall..
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@anjali shared a link, 11 months, 2 weeks ago
Customer Marketing Manager, Last9
Instrument LangChain and LangGraph Apps with OpenTelemetry
Understand how to trace, monitor, and debug LangChain and LangGraph apps using OpenTelemetry, down to chains, tools, tokens, and state flows.
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@faun shared a link, 11 months, 2 weeks ago
FAUN.dev()
I’m Losing All Trust in the AI Industry
AI bigwigs promiseAGIin a quick 1-5 years, but the revolving door at labs like OpenAI screams wishful thinking. As AI hustles to serve up habit-forming products, the priority on user engagement echoes the well-troddensocial mediaplaybook. Who needs productivity, anyway? Cash fuels AI's joyride, with.. read more
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@faun shared a link, 11 months, 2 weeks ago
FAUN.dev()
EU businesses push for freedom from AI rules and competition
Mistral's"AI for Citizens" isn't just about tech; it's about shaking up public services for the better. Meanwhile, in the EU, a plot twist—50 European firms holler for halting the AI Act, all in the name of staying competitive. They argue speed matters more than red tape. But hey, watchdogs eye them.. read more
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@faun shared a link, 11 months, 2 weeks ago
FAUN.dev()
Gemma 3n Introduces Novel Techniques for Enhanced Mobile AI Inference
Gemma 3nshakes up mobile AI with a two-punch combo:Per-Layer Embeddingsthat axe RAM usage andMatFormerthat sends performance into overdrive with elastic inference and nesting.KV cache sharingcranks up the speed of streaming responses, though it taps out at multilingual audio processing for clips up .. read more
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@faun shared a link, 11 months, 2 weeks ago
FAUN.dev()
From Noise to Structure: Building a Flow Matching Model from Scratch
Train a petite neural net to align velocity flows between distributions. DeployFlow Matching lossfor the job. Harness the precision of theAdamoptimizer to keep it sharp... read more
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@faun shared a link, 11 months, 2 weeks ago
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Context Engineering for Agents
Context engineeringcranks an AI agent up to 11 by juggling memory like a slick OS. It writes, selects, compresses, and isolates—never missing a beat despite those pesky token limits. Nail the context, and you've got a dream team. Slip up, though, and you might trigger chaos, like when ChatGPT went r.. read more
BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.
Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.
Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).
