Merge pull request #7280 from jddocs/rc-v1.379.0

[Release Candidate] v1.379.0

Author: jddocs

docs/guides/akamai/solutions/complete-observability-for-live-stream-events-with-trafficpeak/index.md

@@ -5,7 +5,7 @@ description: "This guide discusses the requirements and challenges related to im
 authors: ["John Dutton"]
 contributors: ["John Dutton"]
 published: 2024-07-31
-keywords: ['list','of','keywords','and key phrases']
+keywords: ['observability','trafficpeak','compute','object storage','akamai cloud','datastream','logs','data loggging']
 license: '[CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0)'
 external_resources:
 - '[Akamai Solution Brief: Media TrafficPeak Observability Platform](https://www.akamai.com/resources/solution-brief/trafficpeak-observability-platform)'
@@ -15,7 +15,7 @@ external_resources:
 
 Live streaming events require complete observability in order to deliver a seamless user experience during periods of extreme traffic. Supporting large amounts of concurrent viewers depends on live application and infrastructure insights so that you can troubleshoot issues in real-time.
 
-Complete observability for live streams poses multiple challenges, including implementing data logging at each step, logging storage costs, analyzing data, and timely data reporting. This guide discusses these challenges and considerations, how they can be addressed using TrafficPeak, and a high-level architecture review for achieving live stream observability on Akamai Connected Cloud.
+Complete observability for live streams poses multiple challenges, including implementing data logging at each step, logging storage costs, analyzing data, and timely data reporting. This guide discusses these challenges and considerations, how they can be addressed using TrafficPeak, and a high-level architecture review for achieving live stream observability on Akamai.
 
 The architecture diagram in this guide references a workflow used to stream one of the largest ad-supported sporting events in the world, supporting one of the largest concurrent user bases ever with an average of 18 million concurrent viewers. The observability solution implemented via Akamai DataStream and TrafficPeak was able to ingest, store, organize, and display insights into the entire streaming media workflow, while Akamai CDN delivered the event to end-users.
 
@@ -31,7 +31,7 @@ TrafficPeak’s observability solution allows you to ingest, store, and analyze
 
 Complete observability means logging each step of the live stream process, including ingesting live camera feeds, content storage, content delivery, ad insertion, and user playback. Doing this on a global scale, for millions of concurrent users, can result in processing billions of logs and large cloud bills in a very short amount of time.
 
-TrafficPeak uses a highly efficient compression algorithm that helps store more logs, for longer, and cheaper - up to 75% less than other observability solutions. And since Linode Object Storage, TrafficPeak, and Akamai CDN are all part of Akamai Connected Cloud, egress costs can also be reduced by up to 100%.
+TrafficPeak uses a highly efficient compression algorithm that helps store more logs, for longer, and cheaper - up to 75% less than other observability solutions. And since Linode Object Storage, TrafficPeak, and Akamai CDN are all part of Akamai, egress costs can also be reduced by up to 100%.
 
 ### Log Analysis
 
@@ -54,12 +54,12 @@ TrafficPeak offers sub-second querying and optimizes log indexing with fully cus
 
 ### Systems and Components
 
--   **Akamai DataStream + TrafficPeak:** Akamai’s complete observability solution. DataStream sends logs from the edge to TrafficPeak on compute and object storage, all while on the Akamai Connected Cloud network.
+-   **Akamai DataStream + TrafficPeak:** Akamai’s complete observability solution. DataStream sends logs from the edge to TrafficPeak on compute and object storage running on Akamai Cloud.
 
 -   **Akamai CDN:** Akamai’s industry-leading content delivery network used for caching and global delivery.
 
 -   **Akamai Media Services Live (MSL):** Low-latency ingest of media content for high-quality live streaming.
 
--   **Linode Object Storage:** Cost-effective object storage used for media and log storage on Akamai Connected Cloud.
+-   **Linode Object Storage:** Cost-effective object storage used for media and log storage on Akamai Cloud.
 
--   **Server-Side Ad Insertion (SSAI):** The process of attaching, or stitching, ads to content prior to reaching end-user devices. Ad logs (i.e. ad played and ad interacted) can also be sent to TrafficPeak with the TrafficPeak Video Analytics add-on.
+-   **Server-Side Ad Insertion (SSAI):** The process of attaching, or stitching, ads to content prior to reaching end-user devices. Ad logs (i.e. ad played and ad interacted) can also be sent to TrafficPeak with the TrafficPeak Video Analytics add-on.

docs/guides/akamai/solutions/high-performance-kv-store-fintech-akamai/index.md

@@ -14,7 +14,7 @@ external_resources:
 
 Fintech and eCommerce services process high volumes of transactions and have demanding requirements for performance, reliability, and resiliency. The data storage size for a given transaction in these services may not be as large as in other industries like media or gaming, but they must adhere to rigorous standards for security, latency, and consistency.
 
-This guide outlines a distributed key-value (KV) storage architecture that supports registration for users between a global fintech service and a banking system. In particular, the data stored represents users' credit card information, and it is encrypted in this storage system. This KV store is implemented with NATS and the JetStream persistence engine, and it is deployed across 11 core compute regions on Akamai Connected Cloud. The system is capable of storing hundreds of millions of keys while guaranteeing low latency for registration requests and a resilient method for quickly publishing and updating key-value data.
+This guide outlines a distributed key-value (KV) storage architecture that supports registration for users between a global fintech service and a banking system. In particular, the data stored represents users' credit card information, and it is encrypted in this storage system. This KV store is implemented with NATS and the JetStream persistence engine, and it is deployed across 11 core compute regions on Akamai Cloud. The system is capable of storing hundreds of millions of keys while guaranteeing low latency for registration requests and a resilient method for quickly publishing and updating key-value data.
 
 ## Distributed KV Store Workflow
 
@@ -58,7 +58,7 @@ For this reason, it is important for these update operations to be propagated qu
 
 ## Distributed Key-Value Store Design Diagram
 
-This solution creates a key-value storage service on Akamai Connected Cloud. The service is composed of a primary storage cluster in one compute region and ten storage leaf nodes installed across ten other compute locations. Akamai Global Traffic Management routes requests from users to these leaf nodes.
+This solution creates a key-value storage service on Akamai Cloud. The service is composed of a primary storage cluster in one compute region and ten storage leaf nodes installed across ten other compute locations. Akamai Global Traffic Management routes requests from users to these leaf nodes.
 
 ![NATS Key-Value Store Design Diagram](nats-kv-store.svg?diagram-description-id=nats-kv-store-design-diagram)
 
@@ -93,4 +93,4 @@ This solution creates a key-value storage service on Akamai Connected Cloud. The
 
     The gateway retrieves the value of the key from the corresponding NATS leaf node.
 
-- **[Akamai Global Traffic Management](https://www.akamai.com/products/global-traffic-management)** is responsible for accepting user requests on the service and routing requests to an available leaf node that provides the lowest latency for the user's location.
+- **[Akamai Global Traffic Management](https://www.akamai.com/products/global-traffic-management)** is responsible for accepting user requests on the service and routing requests to an available leaf node that provides the lowest latency for the user's location.

docs/guides/akamai/solutions/iot-firmware-upgrades-with-obj-and-cdn/index.md

@@ -10,7 +10,7 @@ license: '[CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0)'
 ---
 
 ## Overview
-As more and more consumer electronics join the Internet of Things (IoT), the need to deliver feature and security firmware updates to these devices becomes more critical for IoT device manufacturers. One of the main aspects of delivery manufacturers need to plan for is how much egress data these systems will use. At scale, the price of keeping both consumers and the business happy and secure can be enormous. Using Linode Object Storage on Akamai Connected Cloud as an origin for this data, and connecting that service to Akamai CDN, can provide a huge cost savings over other competing hyperscalers.
+As more and more consumer electronics join the Internet of Things (IoT), the need to deliver feature and security firmware updates to these devices becomes more critical for IoT device manufacturers. One of the main aspects of delivery manufacturers need to plan for is how much egress data these systems will use. At scale, the price of keeping both consumers and the business happy and secure can be enormous. Using Linode Object Storage on Akamai Cloud as an origin for this data, and connecting that service to Akamai CDN, can provide a huge cost savings over other competing hyperscalers.
 
 ## Firmware Update Workflow
 1.  A manufacturer uploads a new firmware package to an Object Storage bucket.
@@ -29,7 +29,7 @@ An IoT manufacturer found themselves struggling to send OS and firmware updates
 
 Another challenge the IoT manufacturer encountered was supporting more IoT devices worldwide. This resulted in the scale of their firmware delivery service growing in both storage and delivery costs. The IoT manufacturer was looking for a service that could help them save money on egress and improve their bottom line.
 
-**Solution**: Because Linode Object Storage on Akamai Connected Cloud has much lower egress rates than AWS’ offerings, and because it can be set as an origin for Akamai CDN, the IoT manufacturer was not only able to keep file system access to firmware objects, but decrease egress costs by 90%.
+**Solution**: Because Linode Object Storage on Akamai Cloud has much lower egress rates than AWS’ offerings, and because it can be set as an origin for Akamai CDN, the IoT manufacturer was not only able to keep file system access to firmware objects, but decrease egress costs by 90%.
 
 ## Architecture
 

docs/guides/akamai/solutions/preparing-infrastructure-for-high-impact-ad-traffic/index.md

@@ -1,7 +1,7 @@
 ---
 slug: preparing-infrastructure-for-high-impact-ad-traffic
 title: "Preparing Infrastructure for High-Impact Advertising Traffic on Akamai"
-description: "This guide discusses the infrastructure challenges related to traffic associated with high-impact ad campaigns. It also proposes a reference architecture and strategies used to support surges during high-traffic events on Akamai Connected Cloud."
+description: "This guide discusses the infrastructure challenges related to traffic associated with high-impact ad campaigns. It also proposes a reference architecture and strategies used to support surges during high-traffic events on Akamai."
 authors: ["John Dutton"]
 contributors: ["John Dutton"]
 published: 2024-07-10
@@ -70,7 +70,7 @@ At the edge, Akamai’s [App & API Protector](https://www.akamai.com/products/ap
 
 5.  Queue-it waiting rooms allow for user prioritization and enhance the user experience during periods of extremely high traffic.
 
-6.  TrafficPeak on Akamai Connected Cloud provides near real-time visualization of event data.
+6.  TrafficPeak on Akamai provides near real-time visualization of event data.
 
 7.  Akamai routes CDN traffic through designated edge servers. This allows customers to drop traffic from other sources and prevent attackers from bypassing edge-based protection.
 {#high-impact-ad-arch .large-diagram}
@@ -93,4 +93,4 @@ At the edge, Akamai’s [App & API Protector](https://www.akamai.com/products/ap
 
 -  **Load Testing (CloudTest):** CloudTest is a load testing tool that lets customers run peak traffic performance testing for environments at scale.
 
--  **TrafficPeak:** Akamai’s managed observability solution. Runs on Akamai Connected Cloud and is comprised of Compute Instances, Object Storage, and a visual Grafana dashboard for near real-time monitoring.
+-  **TrafficPeak:** Akamai’s managed observability solution. Runs on Akamai Cloud infrastructure and is comprised of Compute Instances, Object Storage, and a visual Grafana dashboard for near real-time monitoring.

docs/guides/applications/big-data/manually-deploy-kafka-cluster/index.md

@@ -3,8 +3,9 @@ slug: manually-deploy-kafka-cluster
 title: "Manually Deploy an Apache Kafka Cluster on Akamai"
 description: "Learn how to deploy and test a secure Apache Kafka cluster on Akamai using provided, customizable Ansible playbooks."
 authors: ["John Dutton","Elvis Segura"]
-contributors: ["John Dutton","Elvis Segura"]
+contributors: ["John Dutton","Elvis Segura","Philip Tellis","Nathan Melehan"]
 published: 2024-11-20
+modified: 2025-05-29
 keywords: ['apache kafka','kafka','data stream','stream management']
 license: '[CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0)'
 external_resources:
@@ -239,6 +240,9 @@ All secrets are encrypted with the Ansible Vault utility as a best practice.
     -   `region`: The data center region for the cluster.
     -   `image`: The distribution image to be installed on each Kafka instance. The deployment in this guide supports the `ubuntu24.04` image.
     -   `group` and `linode_tags` (optional): Any [groups or tags](/docs/guides/tags-and-groups/) you with to apply to your cluster’s instances for organizational purposes.
+    -   `firewall_label` (optional): The label for a [Cloud Firewall](https://techdocs.akamai.com/cloud-computing/docs/cloud-firewall) that can be created for the cluster. If this label is not provided, the firewall is not created.
+    -   `vpc_label` (optional): The label for a [VPC](https://techdocs.akamai.com/cloud-computing/docs/vpc) that can be created for the cluster. If this label is not provided, the VPC is not created.
+    -   `domain_name` and `ttl_sec` (optional): A domain name and [TTL (in seconds)](https://techdocs.akamai.com/cloud-computing/docs/troubleshooting-dns-records#set-the-time-to-live-or-ttl) for the cluster. Each cluster instance is assigned a subdomain of this domain name. For example, if your domain name is `example.com`, a record named `instance_label.example.com` is created for each instance. If a domain name is not provided, these records are not created.
     -   `cluster_size`: The number of Kafka instances in the cluster deployment. Minimum value of 3.
     -   `sudo_username`: A sudo username for each cluster instance.
     -   `country_name`, `state_or_province_name`, `locality_name`, and `organization_name`: The geographical and organizational information for your self-signed TLS certificate.
@@ -255,6 +259,12 @@ All secrets are encrypted with the Ansible Vault utility as a best practice.
     image: linode/ubuntu24.04
     group:
     linode_tags:
+    firewall_label:
+    vpc_label:
+
+    # Optional settings for DNS
+    domain_name:
+    ttl_sec:
 
     cluster_size: 3
     client_count: 2

docs/guides/kubernetes/deploy-prometheus-operator-with-grafana-on-lke/index.md

@@ -150,13 +150,12 @@ In this section, you will create a Helm chart values file and use it to deploy P
 1.  Using Helm, deploy a Prometheus Operator release labeled `lke-monitor` in the `monitoring` namespace on your LKE cluster with the settings established in your `values.yaml` file:
 
     ```command
-    helm install \
-    lke-monitor stable/kube-prometheus-stack\
+    helm install lke-monitor kube-prometheus-stack \
+    --repo https://prometheus-community.github.io/helm-charts \
     -f ~/lke-monitor/values.yaml \
     --namespace monitoring \
-    --set grafana.adminPassword=$GRAFANA_ADMINPASSWORD \
-    --set prometheusOperator.createCustomResource=false \
-    --repo https://prometheus-community.github.io/helm-charts
+    --set grafana.adminPassword="$GRAFANA_ADMINPASSWORD" \
+    --set prometheusOperator.createCustomResource=false
     ```
 
     {{< note >}}
@@ -653,4 +652,4 @@ Your monitoring interfaces are now publicly accessible with HTTPS and basic auth
 
 When accessing an interface for the first time, log in as `admin` with the password you configured for [basic auth credentials](#configure-basic-auth-credentials).
 
-When accessing the Grafana interface, you will then log in again as `admin` with the password you exported as `$GRAFANA_ADMINPASSWORD` on your local environment. The Grafana dashboards are accessible at **Dashboards > Manage** from the left navigation bar.
+When accessing the Grafana interface, you will then log in again as `admin` with the password you exported as `$GRAFANA_ADMINPASSWORD` on your local environment. The Grafana dashboards are accessible at **Dashboards > Manage** from the left navigation bar.

docs/guides/platform/object-storage/optimizing-obj-bucket-architecture-for-akamai-cdn/index.md

@@ -5,15 +5,15 @@ description: "This guide discusses design strategies and best practices for opti
 authors: ["Akamai"]
 contributors: ["Akamai"]
 published: 2024-09-27
-keywords: ['object storage','cdn','delivery','linode object storage','akamai cdn','akamai connected cloud','bucket architecture']
+keywords: ['object storage','cdn','delivery','linode object storage','akamai cdn','akamai cloud','bucket architecture']
 license: '[CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0)'
 external_resources:
 - '[Object Storage Product Documentation](https://techdocs.akamai.com/cloud-computing/docs/object-storage)'
 - '[Akamai Content Delivery Documentation](https://techdocs.akamai.com/platform-basics/docs/content-delivery)'
 - '[Using Object Storage With Akamai CDN](/docs/guides/using-object-storage-with-akamai-cdn/)'
 ---
 
-Linode Object Storage can be an efficient, cost-effective solution for streaming and data delivery applications when used as an origin point for Akamai CDN. Since Object Storage is a part of Akamai Connected Cloud and uses the same backbone as Akamai CDN, egress can also be significantly reduced.
+Linode Object Storage can be an efficient, cost-effective solution for streaming and data delivery applications when used as an origin point for Akamai CDN. Since Object Storage is a part of Akamai Cloud and uses the same backbone as Akamai CDN, egress can also be significantly reduced.
 
 Your Object Storage bucket architecture is critical to performance success. In particular, distributing content across multiple buckets helps with load distribution, CDN optimization, and adds security benefits like segmentation and origin obfuscation. This guide walks through bucket design strategies using a commerce site example, including an optimal bucket architecture for Akamai CDN integration.
 
@@ -88,4 +88,4 @@ Each bucket in your architecture has the ability to serve as a single origin end
 
 ### Relationship To Bucket Design
 
-CDNs can often overcome flaws of poorly architected environments. However, when a bucket architecture is designed well, the benefits can directly translate to the CDN. Object Storage bucket architecture should be designed to be functional, scalable, performant, resilient, and cost efficient so that Akamai CDN serves your content as effectively as possible.
+CDNs can often overcome flaws of poorly architected environments. However, when a bucket architecture is designed well, the benefits can directly translate to the CDN. Object Storage bucket architecture should be designed to be functional, scalable, performant, resilient, and cost efficient so that Akamai CDN serves your content as effectively as possible.