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@squadcast shared a post, 1 year, 7 months ago

The Impact of MTTR on Customer Satisfaction and Business Success | Squadcast

The blog discusses the importance of Mean Time to Repair (MTTR) in ensuring uninterrupted service and customer satisfaction. MTTR measures the average time taken to resolve a system failure. A lower MTTR leads to higher operational efficiency, cost control, and improved customer experience. Strategies to reduce MTTR include robust monitoring tools, standardized incident response protocols, employee training, automation, and continuous improvement. By focusing on MTTR, businesses can enhance their reputation, reduce downtime costs, and gain a competitive edge.

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@laura_garcia shared a post, 1 year, 7 months ago
Software Developer, RELIANOID

UDP Load Balancing

🌐UDP Load Balancing is a network solution designed to distribute incoming traffic across servers using the User Datagram Protocol (UDP), ideal for applications prioritizing low latency, such as VoIP, online gaming, and live streaming. Unlike TCP, UDP does not require connection establishment or data..

udp load balancing diagram
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@laura_garcia shared a post, 1 year, 7 months ago
Software Developer, RELIANOID

Community Edition weekly downloads chart

🚀 Exciting times at RELIANOID! We've seen a significant surge in downloads of our Community Edition with each release, and this growth has been incredibly motivating for our team. It’s amazing to see the trust and interest from the community, and it fuels our commitment to keep raising the bar. With..

Enterprise Edition descargas semanales
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@laura_garcia shared a post, 1 year, 7 months ago
Software Developer, RELIANOID

Unlock the Power of Global Server Load Balancing (GSLB)

🌍 🌐 Curious about how GSLB optimizes network performance on a global scale? Unlike traditional load balancing, GSLB distributes traffic across multiple regions to ensure high availability, reduce latency, and improve resilience. With RELIANOID's intuitive platform, configuring GSLB is straightforwa..

KB Global server load balancing RELIANOID
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@anjali shared a link, 1 year, 7 months ago
Customer Marketing Manager, Last9

Scaling Prometheus: Tips, Tricks, and Proven Strategies

Learn how to scale Prometheus with practical tips and strategies to keep your monitoring smooth and efficient, even as your needs grow!


Scaling Prometheus
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@adammetis shared a post, 1 year, 7 months ago
DevRel, Metis

3 Hot Trends In Database Reliability

Let’s see 3 hot trends in database reliability that every team should incorporate into their organization.

3 Hot Trends In Database Reliability@3x
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@adammetis shared a post, 1 year, 7 months ago
DevRel, Metis

Things Platform Engineers Lack When Dealing With Databases

Platform engineers focus on all phases of SDLC around databases. However, they lack the tools, processes, and mindset to unleash the power of their teams. Let’s see what they miss and how to change our organizations to move faster.

PlatformEngineers.webp
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@faun shared a link, 1 year, 7 months ago
FAUN.dev()

Reflections on IaC using Terraform

This post provides useful notes and examples on working with infrastructure as code projects using Terraform, focusing on techniques for querying from external providers and structuring variables. It also covers tips on using data blocks, variables, outputs, sensitive variables, locals, iterating ov.. read more  

Reflections on IaC using Terraform
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@faun shared a link, 1 year, 7 months ago
FAUN.dev()

What is DORA, and how does it impact the database?

DORA mandates that by January 2025, financial institutions must demonstrate robust incident management, compliance, and governance by implementing detailed logging, incident response policies, and streamlined database monitoring and patch management... read more  

What is DORA, and how does it impact the database?
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@faun shared a link, 1 year, 7 months ago
FAUN.dev()

Durable Objects aren't just durable, they're fast: a 10x speedup for Cloudflare Queues

Cloudflare Queues allow developers to decouple Workers into event-driven services, increasing performance and scalability for larger workloads. The v2 architecture for Queues leverages multiple Durable Objects for each Queue, reducing latency and increasing message throughput and consumer concurrenc.. read more  

NanoClaw is an open-source personal AI agent designed to run locally on your machine while remaining small enough to fully understand and audit. Built as a lightweight alternative to larger agent frameworks, the system runs as a single Node.js process with roughly 3,900 lines of code spread across about 15 source files.

The agent integrates with messaging platforms such as WhatsApp and Telegram, allowing users to interact with their AI assistant directly through familiar chat applications. Each conversation group operates independently and maintains its own memory and execution environment.

A core design principle of NanoClaw is security through isolation. Every agent session runs inside its own container using Docker or Apple Container, ensuring that the agent can only access files and resources that are explicitly mounted. This approach relies on operating system–level sandboxing rather than application-level permission checks.

The architecture is intentionally simple: a single orchestrator process manages message queues, schedules tasks, launches containerized agents, and stores state in SQLite. Additional functionality can be added through a modular skills system, allowing users to extend capabilities without increasing the complexity of the core codebase.

By combining a minimal architecture with container-based isolation and messaging integration, NanoClaw aims to provide a transparent, customizable personal AI agent that users can run and control entirely on their own infrastructure.