Optimize long-term video storage prices with Amazon Kinesis Video Streams heat storage tier

Introduction

Amazon Kinesis Video Streams offers highly effective options for cloud-based video administration in bodily safety and surveillance organizations. Whereas organizations want steady recording capabilities, conventional storage approaches usually result in elevated prices. Kinesis Video Streams excels at real-time video administration and short-term storage, serving enterprise deployments with in depth digital camera networks. Now, the progressive Kinesis Video Streams heat storage function enhances these capabilities, delivering cost-efficient options for long-term video retention, and enabling organizations to optimize their storage methods.

On this put up, we present how by successfully utilizing the newly launched Kinesis Video Streams heat storage function, you’ll be able to construct a way more cost-efficient answer for long-term video retention whereas sustaining the efficiency and accessibility your operations require.

What did we launch?

On November twenty sixth, 2025, Amazon Kinesis Video Streams added a brand new heat storage tier, delivering cost-effective storage for prolonged media retention. The usual Kinesis Video Streams storage tier (now designated as the new tier) stays optimized for real-time knowledge entry and short-term storage. The brand new heat tier permits long-term media retention with sub-second entry latency at diminished storage prices.

Buyer advantages

Whereas Amazon Kinesis Video Streams scorching storage excels at real-time streaming, regulatory compliance usually requires prolonged retention durations, making it pricey for bodily safety and enterprise video surveillance prospects. Clients that sometimes used Kinesis Video Streams scorching tier for streaming however then moved knowledge to different cost-efficient storage can now hold media in Kinesis Video Streams’ heat tier with out incurring a value penalty. This brings a number of benefits: (a) Clients can preserve less complicated architectures with out managing knowledge migration, scale back their operational overhead, and hold their knowledge readily accessible throughout the Kinesis Video Streams ecosystem. (b) Bigger datasets stay in Kinesis Video Streams, prospects profit from extra full historic knowledge and fewer fragmentation throughout storage programs. This permits enhanced analytics capabilities by means of simpler processing of steady knowledge streams, higher temporal evaluation potential, and streamlined ML/AI mannequin coaching. As well as, ingestion into Kinesis Video Streams heat storage tier is priced per continued fragment depend. Meaning builders management prices by adjusting fragment dimension – bigger fragments scale back ingestion prices, whereas smaller fragments ship decrease latency. This flexibility lets builders optimize their particular use circumstances.

Structure

Amazon Kinesis Video Streams tiered storage structure offers a seamless integration between real-time streaming capabilities and cost-optimized long-term storage. The structure consists of two elements: Video ingestion, that features IoT gadgets and cameras stream video knowledge to KVS endpoints, and the Storage tier. The storage tier choice relies on the stream’s configuration, and fragments are saved in both scorching or heat tier.

Key advantages of this structure are:

• Unified API: Similar Amazon Kinesis Video Streams APIs work throughout each storage tiers
• Seamless playback: Purposes can retrieve video no matter storage tier
• Dynamic configuration: Storage tiers will be modified with out service interruption
• Computerized lifecycle: Constructed-in insurance policies handle knowledge transitions and retention

Price concerns

The desk beneath reveals Amazon Kinesis Video Streams’ scorching and heat tier pricing construction for US East (N. Virginia) area. Word that heat tier storage costs have a major discount whereas consumption prices stay constant throughout each tiers. Heat ingestion is priced based mostly on fragment depend reasonably than per GB, which offers predictable value administration for long-term retention situations. Heat tier storage comes with a 30-day minimal retention interval, that means AWS fees prospects for at the very least 30 days even in the event that they delete the information earlier.

Kinesis Video Streams is constructed on Amazon Easy Storage Service (Amazon S3)’s knowledge retailer, making certain your video knowledge is saved with excessive sturdiness and availability. Nonetheless, the frequency of accessing saved video knowledge can fluctuate considerably throughout totally different use circumstances. For instance, think about a situation the place CCTV uncooked knowledge should be retained for 30 days for safety compliance functions. If no particular occasions happen, the frequency and segments of knowledge that must be reviewed will lower over time. In such conditions, heat tier performance lets you scale back storage prices whereas sustaining the identical sturdiness and availability of storage.

Amazon Kinesis Video Streams’ heat tier is constructed on Amazon S3 Normal-Rare Entry (S3 Normal-IA) to offer the next advantages:

• As much as 67% value discount: Vital value financial savings in comparison with normal Amazon Kinesis Video Streams storage
• Similar sturdiness and availability: 99.999999999% sturdiness and 99.9% availability assure
• Seamless integration: Helps compatibility with present Amazon Kinesis Video Streams workflows and APIs
• Automated lifecycle administration: Automated knowledge administration by means of configurable insurance policies

Now let’s have a look at 3 ways to optimize prices utilizing the nice and cozy tier.

1. Storage duration-based value optimization

Heat tier is designed for value optimization in use circumstances requiring long-term storage. Whereas the nice and cozy tier provides comparatively decrease storage prices, it requires a minimal retention interval of 30 days.

Subsequently, to be used circumstances requiring solely short-term storage, scorching tier could also be less expensive.

Actual-world value evaluation instance: Let’s look at 1,000 CCTV cameras working 8 hours every day:

• Ingestion interval: 30 days
• Bitrate: 4Mbps
• Fragment length: 2 seconds
• AWS Area: us-east-1 area

Price comparability based mostly on retention interval

Key findings: As seen above, beneath the identical fragment size, heat tier value advantages are greater for longer retention durations, sometimes ranging from 30 days.

2. Fragment length-based value optimization

One other progressive function of heat tier is fragment-based billing as an alternative of the standard GB-based billing of scorching tier. This billing strategy permits for important discount in ingestion prices by adjusting fragment size.

The desk beneath reveals how advantages of heat tier improve in comparison with scorching tier when the fragment size will increase. That is for 30-day retention.

Key findings: Beneath the identical retention interval, heat tier advantages are greater for longer fragment lengths. The chart beneath can help as resolution chart. For 30-day retention, heat tier breaks even at fragment size of 1.06 sec, i.e. whole value is cheaper in heat tier vs scorching tier for fragment lengths longer than 1.06 sec. For 60-day retention, that break even occurs at 0.68 sec.

3. Understanding storage value variations by digital camera decision

The nice and cozy tier pricing based mostly on fragment depend mannequin brings value benefits for cameras with greater bitrates. See comparability in desk beneath for 1,000 digital camera deployment over 30 days with 5-second fragments.

Key findings:

• Larger bitrates yield larger financial savings: 4 Mbps streams obtain 48% value discount, whereas 1Mbps streams see 9% financial savings
• Constant ingestion value benefit: Heat tier ingestion stays at $1,687.50 no matter bitrate, whereas scorching tier prices scale linearly with knowledge quantity
• Storage value scaling: Heat tier storage prices scale proportionally with bitrate, however at considerably decrease charges than scorching tier
• Break-even evaluation: All bitrate situations demonstrated substantial value advantages when utilizing Heat tier for prolonged retention durations

This fragment-based pricing mannequin permits considerably less expensive storage and processing of high-resolution video content material with bigger knowledge volumes. The upper the video high quality and bitrate, the extra pronounced the associated fee benefits change into when using heat tier storage.

Storage tier settings

The storage interval settings for present streams will be simply up to date, and the settings are instantly utilized to fragments collected after the replace.Beneath is the AWS CLI command for updating or making a stream in heat tier storage in Amazon Kinesis Video Streams.

Replace storage configuration:

When you have an present stream in scorching tier, you’ll be able to replace the stream settings to heat tier as follows.

```bash 
STREAM_INFO=$(aws kinesisvideo describe-stream 
--stream-name "$STREAM_NAME" 
--region $REGION)

CURRENT_VERSION=$(echo "$STREAM_INFO" | jq -r '.StreamInfo.Model')
aws kinesisvideo update-stream-storage-configuration 
--stream-name "$STREAM_NAME" 
--current-version "$CURRENT_VERSION" 
--stream-storage-configuration DefaultStorageTier="WARM" 
--region $REGION
```

Create stream with heat tier:

You possibly can create a brand new heat tier stream utilizing the next command.

```bash
aws kinesisvideo create-stream 
--stream-name $STREAM_NAME 
--media-type "video/h264" 
--data-retention-in-hours 720 
--stream-storage-configuration '{
"DefaultStorageTier": "WARM"
}' 
--region $REGION
```

The storage interval settings for created streams will be simply modified, and the settings are instantly utilized to fragments collected after the change. Stream playback stays uninterrupted even when storage configuration modifications are utilized.

Cleansing up

To keep away from ongoing fees, be sure to delete the take a look at streams you created throughout this walkthrough. Do not forget that deleting a stream completely removes all saved video knowledge, whatever the storage tier configuration.

Delete the stream:

```bash
STREAM_INFO=$(aws kinesisvideo describe-stream 
--stream-name "$STREAM_NAME" 
--region $REGION)

STREAM_ARN=$(echo "$STREAM_INFO" | jq -r '.StreamInfo.StreamARN')
CURRENT_VERSION=$(echo "$STREAM_INFO" | jq -r '.StreamInfo.Model')

aws kinesisvideo delete-stream 
--stream-arn "$STREAM_ARN" 
--current-version "$CURRENT_VERSION" 
--region $REGION
```

Vital notes:

• Stream deletion is irreversible and removes all related video knowledge
• Each Scorching and Heat tier knowledge can be completely deleted
• Guarantee you will have backed up any necessary video knowledge earlier than deletion
• The deletion course of might take a couple of minutes to finish

Conclusion

Amazon Kinesis Video Streams’ tiered storage functionality delivers an economical strategy for managing video knowledge. By this function organizations can dramatically scale back storage prices whereas sustaining operational excellence. These prices will be managed by controlling three variables: fragment size, retention interval, and determination bitrate. (a) Beneath the identical fragment size, heat tier value advantages are greater for longer retention durations, sometimes ranging from 30 days; (b) beneath the identical retention interval, heat tier advantages are greater for longer fragment lengths; (c) beneath the identical fragment size and retention interval, heat tier value advantages are greater because the bitrates improve.

The important thing to profitable implementation lies in precisely understanding your group’s particular entry patterns, retention necessities, and price optimization targets. Begin with pilot implementation on non-critical streams, monitor outcomes, and steadily increase to your total video infrastructure. Kinesis Video Streams tiered storage isn’t merely a value discount instrument. It’s a strategic enabler that makes sustainable development of video-enabled IoT purposes economically viable.

Subsequent steps

Are you able to optimize prices on your video answer with Kinesis Video Streams tiered storage? Right here’s your path ahead:

In regards to the authors

Andre Sacaguti Andre Sacaguti is a Sr. Product Supervisor at AWS, engaged on Kinesis Video Streams. He helps organizations flip video knowledge into actionable insights, exploring how AI brokers could make streaming video smarter and extra interactive. Earlier than becoming a member of AWS, Andre constructed and launched IoT merchandise at T-Cellular and Qualcomm, serving to linked gadgets work smarter and extra securely.

Jinseon Lee Jinseon Lee is a Senior IoT GTM Options Architect specializing in IoT and Robotics at AWS APJ. With over 12 years of expertise in know-how and software program growth, Jinseon has labored in numerous roles serving to purchasers design and implement optimum cloud architectures.