add Guides pages and update screenshots

content/Cloud/key-value-memory.mdx

@@ -38,4 +38,6 @@ There are two ways to create a new key value instance:
 1. From the Services > Key Value page in the Cloud Console
 2. In code, using the Agentuity SDK
 
+When creating a key value instance from the Cloud Console, click the **Create Storage** button and select **Key Value Store** from the storage type options.
+
 <ThemeImage baseName="keyvalue-new" alt="New Key Value Memory Storage"  />

content/Cloud/meta.json

@@ -6,6 +6,7 @@
 		"agents",
 		"vector-memory",
 		"key-value-memory",
+		"object-storage",
 		"ai-gateway",
 		"settings"
 	]

content/Cloud/object-storage.mdx

@@ -0,0 +1,40 @@
+---
+title: Object Storage
+description: The Object Storage page is for managing your object storage buckets
+---
+
+## Understanding Object Storage
+
+Object storage is designed for storing files, media, and unstructured data, making it ideal for:
+
+- Files and documents
+- Images and videos
+- Backups and archives
+- Static assets
+- Large binary data
+- Public content delivery
+
+## Viewing Your Object Storage Buckets
+
+When you navigate to the Services > Object Store page in the Cloud Console, you'll see a table listing all your object storage buckets with the following information:
+
+- **Bucket Name**: The name of your object storage bucket
+- **Provider**: The storage provider for the bucket
+- **Created At**: When the bucket was created
+- **Size**: The storage size used by the bucket
+- **Num. of Objects**: The number of objects stored in the bucket
+
+You can filter the list of buckets using the search box at the top of the table to quickly find specific buckets by name.
+
+<ThemeImage baseName="object-store" alt="Object Storage Overview" />
+
+## Creating a New Object Storage Bucket
+
+There are two ways to create a new object storage bucket:
+
+1. From the Services > Object Store page in the Cloud Console
+2. In code, using the Agentuity SDK
+
+When creating an object storage bucket from the Cloud Console, click the **Create Storage** button and select **Object Store** from the storage type options. You can also choose your preferred storage provider from the dropdown menu, including Agentuity's built-in storage, Google Cloud Storage, or Azure Blob Storage.
+
+<ThemeImage baseName="object-store-new" alt="New Object Storage" />

content/Cloud/vector-memory.mdx

@@ -37,4 +37,6 @@ There are two ways to create a new vector instance:
 1. From the Services > Vector page in the Cloud Console
 2. In code, using the Agentuity SDK
 
+When creating a vector instance from the Cloud Console, click the **Create Storage** button and select **Vector Database** from the storage type options.
+
 <ThemeImage baseName="vector-new" alt="New Vector Memory Storage"  />

content/Guides/agent-data-handling.mdx

@@ -161,7 +161,7 @@ async def run(request: AgentRequest, response: AgentResponse, context: AgentCont
 
 You must await the `stream` method to get a stream of the raw binary data.  The stream will be a `ReadableStream` object for JavaScript and a `IO[bytes]` object for Python.
 
-See the [Streaming](/guides/agent-streaming) guide for more information on how Agent Streaming works.
+See the [Streaming](/Guides/agent-streaming) guide for more information on how Agent Streaming works.
 
 
 #### Base64

content/Guides/agent-logging.mdx

@@ -0,0 +1,186 @@
+---
+title: Agent Logging
+description: How to use logging in your agents
+---
+
+## What is Agent Logging?
+
+Agent logging provides structured, real-time insights into your agent's execution. Effective logging helps you debug issues, monitor behavior, and understand agent decision-making.
+
+## Logging Interface
+
+The Agentuity platform provides persistent, searchable logs with real-time streaming for all deployed agents.
+
+<ThemeImage baseName="agent-logs" alt="Logs Overview" />
+
+### Log Overview
+
+The Logs dashboard displays:
+
+- **Timestamps**: Precise timing for each log entry
+- **Severity levels**: INFO, WARN, ERROR for categorization  
+- **Source identification**: Which component generated the log
+- **Detailed messages**: Context about agent actions
+
+### Search and Filtering
+
+**AI-Powered Search:**
+Use natural language queries to find log entries. Click the purple sparkle icon and enter your search:
+
+<ThemeImage baseName="agent-logs-filter" alt="AI-Powered Log Search" />
+
+**Filtering Options:**
+- **Severity**: Filter by log level (INFO, WARN, ERROR, etc.)
+- **Project**: Scope logs to specific projects
+- **Agent**: View logs from specific agents
+- **Session ID**: Filter logs for a particular session
+- **Deployment ID**: View logs from specific deployments
+- **Time Range**: Focus on specific time periods
+
+### Detailed Log Analysis
+
+Each log entry provides comprehensive context and can be expanded for full details:
+
+<ThemeImage baseName="agent-logs-detail" alt="Detailed Log Entry View" />
+
+## Logging Best Practices
+
+### 1. Use Appropriate Log Levels
+
+<CodeExample js={`// INFO: Normal flow and state changes
+context.logger.info('Processing user request', { userId, action });
+
+// WARN: Potential issues that don't stop execution
+context.logger.warn('Rate limit approaching', { remaining: 5 });
+
+// ERROR: Failures requiring attention
+context.logger.error('Failed to fetch data', { error: error.message });`} py={`# INFO: Normal flow and state changes
+context.logger.info("Processing user request", user_id=user_id, action=action)
+
+# WARN: Potential issues that don't stop execution
+context.logger.warn("Rate limit approaching", remaining=5)
+
+# ERROR: Failures requiring attention
+context.logger.error("Failed to fetch data", error=str(err))`} />
+
+### 2. Include Relevant Context
+
+Log enough information to understand what happened without re-running:
+
+<CodeExample js={`// Good - includes context
+context.logger.info('Order processed', {
+  orderId: order.id,
+  customerId: customer.id,
+  total: order.total,
+  itemCount: order.items.length
+});
+
+// Less helpful
+context.logger.info('Order done');`} py={`# Good - includes context
+context.logger.info(
+    "Order processed",
+    order_id=order.id,
+    customer_id=customer.id,
+    total=order.total,
+    item_count=len(order.items)
+)
+
+# Less helpful
+context.logger.info("Order done")`} />
+
+### 3. Log Decision Points
+
+Help future debugging by logging key decisions:
+
+<CodeExample js={`if (useCache) {
+  context.logger.info('Using cached response', { 
+    cacheKey, 
+    age: cacheAge 
+  });
+} else {
+  context.logger.info('Cache miss, fetching fresh data', { 
+    cacheKey,
+    reason: 'expired' 
+  });
+}`} py={`if use_cache:
+    context.logger.info(
+        "Using cached response", 
+        cache_key=cache_key, 
+        age=cache_age
+    )
+else:
+    context.logger.info(
+        "Cache miss, fetching fresh data", 
+        cache_key=cache_key,
+        reason="expired"
+    )`} />
+
+### 4. Avoid Logging Sensitive Data
+
+Never log passwords, tokens, or personal information:
+
+<CodeExample js={`// Don't log sensitive data
+context.logger.info('User authenticated', { userId });
+
+// Not this
+context.logger.info('Login attempt', { 
+  username, 
+  password  // Never log passwords!
+});`} py={`# Don't log sensitive data
+context.logger.info("User authenticated", user_id=user_id)
+
+# Not this
+context.logger.info(
+    "Login attempt", 
+    username=username, 
+    password=password  # Never log passwords!
+)`} />
+
+### 5. Use Child Loggers for Request Context
+
+Create child loggers to automatically include context in all related logs:
+
+<CodeExample js={`// Create a child logger with request context
+const requestLogger = context.logger.child({ 
+  requestId: req.id, 
+  userId: req.userId,
+  endpoint: req.path
+});
+
+// All logs from this logger include the context
+requestLogger.info('Starting request processing');
+requestLogger.info('User authenticated');
+requestLogger.error('Failed to fetch user data', error);`} py={`# Create a child logger with request context
+request_logger = context.logger.child(
+    request_id=req.id,
+    user_id=req.user_id,
+    endpoint=req.path
+)
+
+# All logs from this logger include the context
+request_logger.info("Starting request processing")
+request_logger.info("User authenticated")
+request_logger.error("Failed to fetch user data", error=str(e))`} />
+
+## Structured Logging
+
+Use structured data for easier parsing and analysis:
+
+<CodeExample js={`// Structured approach
+context.logger.info('API call completed', {
+  endpoint: '/api/users',
+  method: 'GET',
+  duration: 234,
+  status: 200,
+  userId: req.userId
+});`} py={`# Structured approach
+context.logger.info(
+    "API call completed",
+    endpoint="/api/users",
+    method="GET",
+    duration=234,
+    status=200,
+    user_id=req.user_id
+)`} />
+
+For more observability features, see [Agent Telemetry](/Guides/agent-telemetry) and [Agent Tracing](/Guides/agent-tracing).

content/Guides/agent-telemetry.mdx

@@ -0,0 +1,72 @@
+---
+title: Agent Telemetry
+description: How to use telemetry in your agents
+---
+
+## What is Agent Telemetry?
+
+Agent telemetry provides performance metrics and execution traces for your agents through OpenTelemetry integration. Monitor how your agents perform, where time is spent, and identify optimization opportunities.
+
+## Production Sessions and Analytics
+
+The Agentuity platform provides comprehensive telemetry for deployed agents through the Sessions interface. All production agent executions are automatically tracked and persist for analysis and troubleshooting.
+
+<ThemeImage baseName="sessions" alt="Production Sessions Overview" />
+
+### Session Overview
+
+The Sessions dashboard displays:
+
+- **Status indicators**: Success, failure, and execution state
+- **Agent identification**: Which agent handled each request
+- **Performance metrics**: Duration and cost per session
+- **Timeline data**: When sessions occurred with precise timestamps
+
+### Detailed Session Analysis
+
+Each session provides detailed execution traces with comprehensive telemetry data:
+
+<ThemeImage baseName="agent-session-detail" alt="Detailed Session Timeline with Spans" />
+
+## Understanding Spans
+
+Telemetry data is organized into spans representing units of work. The timeline visualization uses color coding:
+
+- **Root** (Black): Overall agent execution
+- **API/HTTP** (Teal): External service calls
+- **AI Services** (Purple): Language model interactions  
+- **Vector** (Light Blue): Vector database operations
+- **KV** (Orange): Key-value storage operations
+- **LLM** (Pink): LLM-specific operations
+- **Other** (Gray): Miscellaneous operations
+
+Each span includes:
+- Start and end timestamps
+- Duration in milliseconds
+- Relevant attributes (model used, tokens consumed, etc.)
+- Parent-child relationships
+
+### Viewing Span Details
+
+Click on any span in the timeline to view detailed information in the sidebar:
+
+<ThemeImage baseName="agent-session-detail-sidebar" alt="Span Detail Sidebar" />
+
+## Performance Analysis
+
+Use telemetry to identify bottlenecks:
+
+1. **Long-running spans**: Operations taking excessive time
+2. **Sequential operations**: Tasks that could run in parallel
+3. **Repeated calls**: Opportunities for caching
+4. **Token usage patterns**: Optimize prompt efficiency
+
+## OpenTelemetry Integration
+
+Agentuity uses OpenTelemetry standards, enabling:
+- Export to external observability platforms
+- Custom span creation for business logic
+- Correlation across distributed systems
+- Industry-standard tooling compatibility
+
+For implementation details and code examples, see our SDK documentation for [JavaScript](/SDKs/javascript) and [Python](/SDKs/python).