Create temporal.io

src/content/docs/case-study/temporal.io

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+---
+title: temporal.io workflow orchestration platform case study
+author: Adlan Ilyasov <IlyaAdlan>
+tags: temporal, workflow, orchestration, backend, distributed-systems
+---
+
+# Temporal.io Case Study: Workflows That Won't Let You Down
+
+## What Even is Temporal?
+
+So I stumbled on Temporal.io while looking for ways to make our backend more reliable - and man, this thing is cool. It's like if your regular backend workflows had a safety net. Originally built by the same folks who made AWS Step Functions, but way more flexible.
+
+Big names like Uber and Netflix use it for important stuff like payments and ride matching. The key thing? Your workflows **never** die, even if servers crash. As someone who's lost sleep over failed transactions, that got my attention.
+
+## A Bit of Backstory
+
+- 2019: Some smart ex-AWS engineers (including Maxim Fateev) built it
+- 2021: Went open source which was huge
+- 2024: Now has better Python/Go support and plays nice with Kubernetes
+
+## The Good Stuff
+
+Here's why I think Temporal stands out:
+
+### 1. It's Like Time Travel for Your Code
+You know when your server crashes mid-process? With Temporal, it picks up right where it left off. No more:
+- Duplicate orders
+- Half-completed signups
+- "Did that payment go through?" moments
+
+### 2. You Can Write Real Code
+Unlike AWS Step Functions where you're stuck with JSON configurations, Temporal lets you use actual programming languages:
+
+```python
+@workflow.defn
+class OrderWorkflow:
+    async def run(self, order_id: str):
+        try:
+            await payment_processing(order_id)  # This will retry if fails!
+            await ship_order(order_id)
+        except Error as e:
+            await send_failure_email(order_id)
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+## The Beauty of Temporal
+
+The beauty? If the conversion fails at 3AM, Temporal picks it right back up. No more waking up to failed jobs.
+
+## Real-World Use Cases
+
+From what I've seen, Temporal shines for:
+
+### 1. Financial Systems
+- Payment processing that can't fail
+- Fraud detection pipelines
+- Reconciliation jobs
+
+### 2. E-commerce
+- Order fulfillment that survives outages
+- Inventory management
+- Abandoned cart recovery
+
+### 3. DevOps
+- Deployment orchestration
+- Data pipeline management
+- Backup operations
+
+## The Good, The Bad, and The Ugly
+
+### 👍 Why I Like It
+- **Reliability**: Stuff actually completes
+- **Visibility**: See every workflow's status
+- **Flexibility**: Use real code, not just YAML
+
+### 👎 Pain Points
+- **Learning Curve**: Took me 2 weekends to get comfortable
+- **Operational Overhead**: Need to run the Temporal server
+- **Debugging**: Can be tricky when things go wrong
+
+## Alternatives Compared (Chatgpt provided this "graph")
+
+| Tool                | Best For            | Why Temporal Might Be Better        |
+|---------------------|---------------------|-------------------------------------|
+| AWS Step Functions  | AWS shops           | More coding flexibility             |
+| Airflow             | Scheduled jobs      | Better for real-time ops            |
+| Celery              | Simple tasks        | Built-in retries & state            |
+
+## Should You Use Temporal? (Based on My Research)
+
+After digging through docs, case studies, and developer forums, here's what I've learned about when Temporal makes sense:
+
+**Consider Temporal when:**
+- Your application **can't afford lost workflows** (payments, medical systems, etc.)
+- You're currently **writing tons of retry/recovery code** for failed operations
+- Your team has **bandwidth to learn** a new paradigm (it's not plug-and-play)
+
+**Probably overkill for:**
+- Simple **scheduled tasks** (cron jobs handle these fine)
+- Teams without **distributed systems experience** (there's a learning curve)
+- Projects where **"good enough" reliability** is acceptable
+
+## Where I Found the Best Info
+
+1. [Temporal Documentation](https://docs.temporal.io/) - The concepts section helped most
+2. [Uber's Engineering Blog](https://eng.uber.com/) - Real war stories about why they built it
+3. [Community Discussions](https://community.temporal.io/) - Saw actual pain points people hit
+4. [ChatGPT] Helped with writing this in a fitting way for Github

src/content/docs/temporal.io

@@ -0,0 +1,107 @@
+---
+title: temporal.io workflow orchestration platform case study
+author: Adlan Ilyasov <IlyaAdlan>
+tags: temporal, workflow, orchestration, backend, distributed-systems
+---
+
+# Temporal.io Case Study: Workflows That Won't Let You Down
+
+## What Even is Temporal?
+
+So I stumbled on Temporal.io while looking for ways to make our backend more reliable - and man, this thing is cool. It's like if your regular backend workflows had a safety net. Originally built by the same folks who made AWS Step Functions, but way more flexible.
+
+Big names like Uber and Netflix use it for important stuff like payments and ride matching. The key thing? Your workflows **never** die, even if servers crash. As someone who's lost sleep over failed transactions, that got my attention.
+
+## A Bit of Backstory
+
+- 2019: Some smart ex-AWS engineers (including Maxim Fateev) built it
+- 2021: Went open source which was huge
+- 2024: Now has better Python/Go support and plays nice with Kubernetes
+
+## The Good Stuff
+
+Here's why I think Temporal stands out:
+
+### 1. It's Like Time Travel for Your Code
+You know when your server crashes mid-process? With Temporal, it picks up right where it left off. No more:
+- Duplicate orders
+- Half-completed signups
+- "Did that payment go through?" moments
+
+### 2. You Can Write Real Code
+Unlike AWS Step Functions where you're stuck with JSON configurations, Temporal lets you use actual programming languages:
+
+```python
+@workflow.defn
+class OrderWorkflow:
+    async def run(self, order_id: str):
+        try:
+            await payment_processing(order_id)  # This will retry if fails!
+            await ship_order(order_id)
+        except Error as e:
+            await send_failure_email(order_id)
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+## The Beauty of Temporal
+
+The beauty? If the conversion fails at 3AM, Temporal picks it right back up. No more waking up to failed jobs.
+
+## Real-World Use Cases
+
+From what I've seen, Temporal shines for:
+
+### 1. Financial Systems
+- Payment processing that can't fail
+- Fraud detection pipelines
+- Reconciliation jobs
+
+### 2. E-commerce
+- Order fulfillment that survives outages
+- Inventory management
+- Abandoned cart recovery
+
+### 3. DevOps
+- Deployment orchestration
+- Data pipeline management
+- Backup operations
+
+## The Good, The Bad, and The Ugly
+
+### 👍 Why I Like It
+- **Reliability**: Stuff actually completes
+- **Visibility**: See every workflow's status
+- **Flexibility**: Use real code, not just YAML
+
+### 👎 Pain Points
+- **Learning Curve**: Took me 2 weekends to get comfortable
+- **Operational Overhead**: Need to run the Temporal server
+- **Debugging**: Can be tricky when things go wrong
+
+## Alternatives Compared (Chatgpt provided this "graph")
+
+| Tool                | Best For            | Why Temporal Might Be Better        |
+|---------------------|---------------------|-------------------------------------|
+| AWS Step Functions  | AWS shops           | More coding flexibility             |
+| Airflow             | Scheduled jobs      | Better for real-time ops            |
+| Celery              | Simple tasks        | Built-in retries & state            |
+
+## Should You Use Temporal? (Based on My Research)
+
+After digging through docs, case studies, and developer forums, here's what I've learned about when Temporal makes sense:
+
+**Consider Temporal when:**
+- Your application **can't afford lost workflows** (payments, medical systems, etc.)
+- You're currently **writing tons of retry/recovery code** for failed operations
+- Your team has **bandwidth to learn** a new paradigm (it's not plug-and-play)
+
+**Probably overkill for:**
+- Simple **scheduled tasks** (cron jobs handle these fine)
+- Teams without **distributed systems experience** (there's a learning curve)
+- Projects where **"good enough" reliability** is acceptable
+
+## Where I Found the Best Info
+
+1. [Temporal Documentation](https://docs.temporal.io/) - The concepts section helped most
+2. [Uber's Engineering Blog](https://eng.uber.com/) - Real war stories about why they built it
+3. [Community Discussions](https://community.temporal.io/) - Saw actual pain points people hit
+4. [ChatGPT] Helped with writing this in a fitting way for Github