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ExternalSoftware Engineering
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Walk-forward testing, explained honestly

Walk-forward analysis is called the gold standard of strategy validation — but two different things share the name. Know which one you are actually getting. Ask a quant how they validate a strategy and sooner or later you will hear “walk-forward.” It is routinely described as the gold standard for robust testing. That reputation is deserved — and it hides a confusion worth clearing up, because two different things travel under the same name. The classic method, presented by Robert Pardo in 1992,

backtestingquanttrading
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ExternalSoftware Engineering
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How to Keep an AI Product Online When Your Model Provider Goes Down: LLM Failover, Gateways, and Fallback Models

Keep an AI product online by putting an OpenAI-compatible gateway in front of every model call, configuring fallback chains across providers, regions, and a self-hosted open-weight model, and handling timeouts, rate limits, and partial failures in the client. Then run the gateway and your agent services in more than one region so the resilience layer is not itself a single point of failure; Control Plane’s template catalog includes a LiteLLM gateway and a vLLM model server, each deployed once pe

aillmdevops
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ExternalSoftware Engineering
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Kubernetes Secrets Are Distribution, Not Custody

This is article 4 of 10 in Beyond Kubernetes Defaults. Read article 3: A Kubernetes Lease Is Not a Fencing Token first, or start with article 1: When Kubernetes Primitives Aren’t Enough. Later articles cover workload admission and more. Kubernetes Secrets are not the villain of this article. They are a useful API for delivering sensitive configuration to workloads, and they can be protected with encryption at rest, RBAC, admission controls and careful operational practice. The mistake is asking

kubernetessecuritydevops
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ExternalSoftware Engineering
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How to Run an App Across Multiple Regions: Routing, Databases, and Failover for Stateful Workloads

Run an app across regions by deploying the same stateless services from one definition to every region, putting a health-checked global routing layer in front that sends each user to the nearest healthy region, and choosing a data topology per database (single primary with replicas, multi-primary, or distributed SQL) based on how much write latency and data loss you can accept. Failover for stateless services is a routing change, while failover for databases is a promotion that must be designed

clouddevopsdatabase
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ExternalSoftware Engineering
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How to Test Failover Without Taking Production Down: Game Days, Chaos Experiments, and a Region-Failure Drill

Test failover safely by climbing a ladder from tabletop exercises and staging tests to small, reversible production experiments with a limited blast radius, explicit abort conditions, and a rollback path ready. Then run scheduled region drills that prove the architecture works. The safest designs are active-active because traffic already flows through every region; on Control Plane, a workload in a Global Virtual Cloud (GVC), Control Plane’s term for a set of locations a workload runs across, ru

devopssrecloud
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ExternalSoftware Engineering
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LogCarverGuard, an MCP proxy between an AI agent and SQL Server

I am a SQL Server DBA and I also write C# and .NET. Many people now let an AI coding agent like Claude Code or Cursor run SQL on a real database. I wanted something between the agent and the server, so I built LogCarverGuard. This post covers the free edition: what it blocks, how it decides, and what it does not do. It is early. The version is 0.1. The agent talks MCP to the proxy, and the proxy talks to SQL Server. AI agent --(MCP, API key)--> LogCarverGuard proxy --(EXECUTE AS the caller's own

sqlserveraisecurity
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ExternalSoftware Engineering
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Cheapest per token is not cheapest per finished job: what 2,400 runs show

A model with a 33% pass rate turned out to be the cheapest way to finish a task in a recent 10-model benchmark. The same benchmark shows why that result is less of a free lunch than it looks. Here is the metric behind it and how to compute it on your own prompts. The metric Cost per successful task = everything the model spent across every attempt (failed, retried, timed out) divided by the number of attempts that passed. Per-token price cannot see retries, malformed outputs or runs that never f

llmaibenchmark
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ExternalSoftware Engineering
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Keyword Research in Python: Ideas, Search Volume, Difficulty and Intent for ~$3 per 1,000 Keywords

Most keyword research comes down to one loop: start from a few seed terms, expand them into everything people actually search, then keep the ones with real volume and a difficulty you can win. Here's how to run that loop from code, paying per keyword instead of per month, plus what a real run returns and where the data falls short. Disclosure: we (SteadyScrape) built the tool below and get paid when it's used. Keyword Research Tool: Ideas, Volume, KD & Intent (steady-scrape/keyword-research-expl

seopythonmarketing
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