LOCKEDIN / FORWARD-DEPLOYED ENGINEERING 101
Understand it.
Then build it.
You can be an experienced engineer and still be new to agents. Start with what each thing is and how it helps a person do useful work. Explore 48 original introductions across software, agents, cloud, security and delivery. Start here without a model key; each topic connects to deeper instruction and practice.
- 101UnderstandPlain language, visual walkthrough, vocabulary
- 102Build with guidanceOriginal lessons, examples and knowledge checks
- 103Practise and explainRunnable labs, failure cases and handover
- 01Map the workload
- 02Bind identity and data
- 03Prove operation
A deployment and operating environment
What changes when AI runs in a cloud?
A cloud platform provides managed computing, storage, networking and identity services. A managed model endpoint is one service inside that environment. Building AI in a cloud means connecting these pieces into an application with explicit data, access, operational and cost boundaries.
An FDE must design for the customer's actual environment rather than assume every provider exposes the same behavior.
CONNECT IT TO WHAT YOU KNOW
Start with something familiar.
Moving into a managed building saves you from constructing the building. You still choose the rooms, access rules, equipment and operating procedures for your business.
Managed infrastructure reduces some work; it does not establish your application's permissions, quality or compliance. Model access and feature availability vary by region, deployment and account.
Words worth knowing
- Region
- A geographic deployment location offered by a cloud provider.
- Managed service
- A service whose underlying operation is partly handled by the provider.
- Quota
- A provider-enforced limit on resource use.
ONE EXAMPLE / FICTIONAL CASE
Watch the work take shape.
The same maintenance workflow must fit a customer's approved region, private data service and workload identity.
- 01Map the workload
- 02Bind identity and data
- 03Prove operation
Map the workload
Separate application compute, model inference, source storage and durable review state.
A deployment inventoryFROM RECOGNITION TO REASONING
Design one portable workload before choosing a provider.
- 01
List each service responsibility without product names.
- 02
Map the responsibilities to one approved cloud.
- 03
Record one capability you must verify rather than assume.
A responsibility-to-service map and a verification list.
Compare your reasoning when you are ready
Portability starts with explicit contracts. Matching an API shape does not guarantee matching model behavior, IAM, networking or data handling.
Keep notes in your own working copy. Moving through these cards does not record completion.
TURN THE IDEA INTO USEFUL WORK
You can now go deeper.
Managed infrastructure reduces some work; it does not establish your application's permissions, quality or compliance. Model access and feature availability vary by region, deployment and account.
Academy lessons use your existing training access. Free guides stay open.