Add truncation markers to 8 blog posts

Co-authored-by: jordanstephens <[email protected]>

Author: Copilot

blog/2025-06-16-crew-ai-sample.md

@@ -15,6 +15,8 @@ If this sounds familiar (or if you're dreading the prospect of dealing with it),
 You can [find it here](https://github.com/DefangSamples/sample-crew-django-redis-postgres-template).
 :::
 
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 ## A Demo in 60 Seconds
 
 Imagine you're building a system. It might use multiple LLM calls. It might do complex, branching logic in its prompts. It might need to store embeddings to retrieve things in the future, either to pull them into a prompt, or to return them outright. It might need to store other records that don't have embeddings. Here's a very lightweight version of a system like that, as a starting point:

blog/2025-06-16-docker-compose-defang.md

@@ -26,6 +26,8 @@ Our whitepaper dives deep into how Docker Compose paired with Defang significant
 
 Discover how Docker + Defang can simplify your journey from local development to production-ready deployments across your preferred cloud providers.
 
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 import Link from '@docusaurus/Link';
 
 <div style={{marginTop: '2rem', marginBottom: '2rem'}}>

blog/2025-08-07-defang-ai-devops-agent.md

@@ -24,6 +24,8 @@ While AI-powered tools make building apps a breeze, deploying them to the cloud
 
 The bottleneck is no longer the code. It's the infrastructure.
 
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 ## Enter Defang: Your AI DevOps Agent
 
 **Defang** is an AI-enabled agent that takes care of your entire deployment workflow, going from app code to a production-ready deployment on your favorite cloud in a single step.

blog/2025-08-12-july-product-updates.md

@@ -22,6 +22,8 @@ author: Defang Team
 
 July was all about making cloud deployments even smoother and smarter. We focused on removing friction from deployments and giving you better visibility into costs. Railpack now builds production-ready images automatically when no Dockerfile is present, and our real-time cost estimation feature now supports Google Cloud alongside AWS. We also added managed MongoDB on GCP, introduced an Agentic LangGraph sample, and connected with builders at Bière & Code & Beer MTL. Here’s what’s new.
 
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 ## Railpack Integration
 
 We’ve integrated [Railpack](https://docs.defang.io/docs/concepts/railpack) into Defang to make deployments even smoother. Railpack automatically builds OCI-compliant images from your source code with minimal configuration. This helps eliminate one of the most common issues our users face: missing or invalid Dockerfiles, especially when they’re generated by LLMs or created by users with limited Docker experience. Now, if no Dockerfile is provided, Defang will seamlessly use Railpack to build a working image for you, so you can focus on your code, not your container setup.

blog/2025-08-22-agentic-apps.md

@@ -25,6 +25,8 @@ Now you are not just building agents; you are picking the right infrastructure,
 
 The result: weeks of DevOps headaches, lost momentum, and engineers stuck wiring infrastructure instead of shipping agents.
 
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 ## We Made it Simple with Cloud Native Support for Agentic Apps
 
 That’s where Defang comes in. We make it easy to deploy full-stack agentic apps to your cloud of choice: native, secure, and scalable.

blog/2025-09-09-august-product-updates.md

@@ -23,6 +23,8 @@ author: Defang Team
 
 August was about making migrations smoother and showing how you can already use Defang to deploy agentic apps at scale. We expanded our sample projects for popular multi-agent frameworks like CrewAI, LangGraph, Autogen, and Strands, validating them on Playground, AWS, and GCP so you can run multi-agent workloads in production without extra DevOps. Our new Heroku migration flow inspects dynos and add-ons, generates a clean Compose file, provisions managed equivalents like Postgres and Redis, and ships to your own cloud in one command. This cuts costs and removes lock-in. We also introduced MCP BYOC prompts so you can deploy to AWS and GCP straight from your IDE. Railpack on GCP now delivers faster, more reliable no-Dockerfile builds with clearer logs and closer parity with AWS.
 
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 ## Heroku Migration
 
 As more and more teams are moving away from legacy PaaS solutions, looking for more flexibility and more control, we’ve made it easier for teams to move off [Heroku](https://docs.defang.io/docs/tutorials/migrating-from-heroku). Defang now supports deployments without a Dockerfile and Defang will even generate a compose file from your Heroku application. The result is a smoother path to AWS or GCP with more features, lower costs, and no lock-in.

blog/2025-09-15-agentic-era.md

@@ -21,6 +21,8 @@ Over the past few decades, the software industry has gone through multiple major
 
 This is not a small adjustment. It is the foundation of how the next generation of software will be trusted and adopted.
 
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 ## **Why the Agentic Era Changes the Rules**
 
 AI products are not like SaaS tools. They do not just manage workflows, they ingest and act on the crown jewels of a business. To succeed in this environment, three conditions must hold true:

blog/2025-09-25-heroku-migration.md

@@ -16,6 +16,8 @@ But convenience has a cost. As your product grows, you want more control over pe
 
 This trade‑off eventually becomes untenable. Teams need the simplicity of a platform like Heroku *and* the power and trust of running inside their own AWS account. This post unpacks why migrating off Heroku matters, highlights the friction points when you try to move to AWS yourself, and shows how the **Defang CLI** bridges the gap.
 
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 ## **Heroku vs. AWS**
 
 Heroku is a Platform‑as‑a‑Service very focused on simplicity and ease of use, while AWS offers a huge array of extremely powerful services that can be difficult to navigate alone. What you get from Heroku is the ability to deploy your application with a simple git push, scale by adding dynos and pick from a marketplace of add‑ons. But you miss out on much of the power of AWS, like the ability to organize and network services the way you want, the ability to deploy in a huge number of regions, their reliability, and much of the control you need to be called enterprise-ready. AWS also tends to be more cost effective as you scale and offers a wide variety of scalable storage options including Postgres, MongoDB, Redis, and more.