Tengxun cloud account purchase: video transcoding, whether to choose computing or standard server?

cloud 2026-06-23 阅读 35

For video website bloggers, online education entrepreneurs and webmasters of overseas short video platforms, "video transcoding" will always be the number one beast that consumes computing power.

The original recorded video files are usually very high bit rate, format clutter (such as MOV, MKV, etc.). In order to allow users to play smoothly in different network environments and not blindly consume server bandwidth, webmasters must uniformly compress them into MP4 or HLS(m3u8) format encoded by H.264/H.265 through transcoding.

In the ecology of Tengxun Cloud, if you decide to build your own transcoding server (for example, using FFmpeg scheme), you will inevitably face a classic architecture problem when creating cloud server CVM:

Should I choose a Compute (e. g., C- Series) or Standard (e. g., S-Series) server?

As a blogger who has been struggling with cloud architecture for many years and is increasing SEO weight by optimizing independent stations every day, I will start today from the aspects of computing power architecture, transcoding performance, financial cost (FinOps) and

SEO landing

Four dimensions, for you to thoroughly explain this problem.

1. core conclusions first: according to the business scenario "in the seat"

If you don't want to look at the technical parameters of the long talk, the following are the architectural conclusions that can be directly applied:

The preferred computing type (C series): if your website is a short video, high-frequency UGC (user contribution), high-definition movie station, the core pain point is "after the video is uploaded, transcoding must be completed and online as soon as possible".

Alternative Standard Type (S Series): If your business is cold video archiving, low-frequency updated personal blogs, and batch transcoding at night, you are more concerned about the comprehensive cost performance of data processing per GB.

2. Bottom Computing Power Dismantling: Computational vs Standard

Why transcoding prefers computing? This needs to start with the hardware architecture design of Tencent Cloud Server.

1. Computational examples (e. g. C6, C7 series)

Hardware ratio: The ratio of CPU to memory is usually fixed at 1:2 (such as 4-core 8G and 8-core 16G).

Computing power characteristics: The CPU of the computing instance usually uses the latest generation of high-frequency processors and provides 100 percent exclusive computing power. Crucially, it has excellent support for hardware-accelerated instruction sets such as AVX-512 (Advanced Vector Extensions).

Transcoding advantages: Video transcoding (such as H.264 encoding matrix calculation) is a typical CPU-intensive (Compute-bound) task. During the transcoding process, the CPU is almost continuously at 100 percent full load, while the memory consumption is very small. The ratio of calculation type 1:2 is perfect to spend every penny on the blade of CPU.

2. Standard examples (such as S6, S7 series)

Hardware ratio: The ratio of CPU to memory is usually fixed at 1:4 (such as 4-core 16G, 8-core 32G).

Calculation force characteristic: standard

The quasi-type belongs to the "all-round player" with large memory capacity and strong network packet throughput.

Transcoding Disadvantages: If you use standard transcoding, when the CPU goes up to 100, the redundant memory (the extra 1:4 space) is usually less than 20% used. This means that you pay a high share of the free memory for nothing.

Comparison of 3. Actual Combat Data: Transcoding Efficiency and Large Unit Price PK

In order to give you a more intuitive feeling, we assume that FFmpeg is used to encode a 1080P, 60-frame HD original video with H.265 compression:

Indicator

Computing server (taking 8 cores 16G as an example)

Standard server (take 8 cores 32G as an example)

CPU full load performance

Continuous 100% operation, high frequency, single core processing speed

Continuous 100% operation, slightly lower main frequency

Time-consuming transcoding

Less time consuming (thanks to high frequency and vector instruction set)

Time-consuming relative lengthening $15\% - 25\%$

Memory Idle Rate

Memory utilization is reasonable (about 4-6GB resident)

Serious waste (10GB more + memory idle)

Comprehensive calculation force cost performance

Extremely high (complete tasks in less time, free up resources)

Lower (tasks drag on and are paying for idle memory)

Architect tip: Video transcoding tasks are often charged by time (if it is a pay-as-you-go instance) or calculated by total energy consumption. Although the unit price of a compute instance is slightly higher due to its good CPU performance, the overall bill is often cheaper than that of the standard instance in the pay-as-you-go scenario because of its fast transcoding speed and early completion.

4. webmaster avoids the pit: how to use "tengxunyun account purchase" to push the cost to the extreme?

Video transcoding cluster is a well-known "banknote crushing machine". Blind purchase of servers at original prices can easily lead to project bankruptcy. Want to get the transcoding cost down, the webmaster is doing it.

Tencent Cloud Account Purchase

When planning with resources, be sure to learn the following two sets of FinOps combinations:

1. Standardize the purchase of Tengxun cloud accounts and lock in new customers and enterprise privileges

Before the project starts, be sure to register and complete a new one through formal channels.

Tencent Cloud Account Purchase

With the enterprise real name authentication. Tengxunyun officials often give an amazing discount of 1-2% for newly registered accounts (especially enterprise authentication accounts) in the "big promotion special offer" or "peer plan.

Avoidance: Transcoding services are extremely dependent on disk I/O (reading and writing original files and output files). When purchasing ECS instances under Tengxun Cloud account, disks must be equipped with high-performance cloud disks or SSD cloud disks. If the basic cloud disk is selected by mistake, the disk read and write run is not satisfied. Even if you buy a good computing CPU, the computing power will be blocked in the disk I/O queue.

2. Ultimate Architecture Solution: Computational "Preemptible Instance"

Because video transcoding is usually an "offline, retry" task (that is, if the transcoding fails, run it again in a big deal, it will not affect the previous

station user access), so the best money-saving solution is:

Money-saving principle: Preemptive instances are ultra-low-cost instances provided by Tengxun Cloud using idle physical machine computing power, and their prices are often only 1-2 percent of the pay-as-you-go.

Architecture design: Use preemptive computing C series servers to build transcoding nodes and store COS with objects. Once the instance is forcibly recycled by the system, the transcoding task is automatically retriggered through the queue (such as CMQ/Kafka). This set of architecture can reduce your overall transcoding cost by $80\%$!

5. the private words of bloggers proficient in SEO: video transcoding and website weight

Many webmasters think transcoding is just a background technology, and SEO (search engine optimization) is playing.

Big mistake!

From an SEO perspective, transcoding speed directly determines your

Timeliness of page launch (Freshness Score)

Seize hot spot traffic: for news, entertainment and evaluation video blogs, whoever can release the latest high-definition video on the whole network first can be captured and included by Google/Baidu spider first. The ultimate transcoding speed brought by the computing server allows you to take the lead in sudden hot spots.

Core Web Vitals (Core Web Vitals): The volume of video encoded and transcoded by computing server depth H.265/AV1 can be reduced by more than 50%, and the image quality is almost lossless. This allows your mobile users to instantly load videos under 3G/4G networks, greatly reducing the bounce rate (Bounce Rate). In the search engine algorithm, low bounce rate and high page stay time are bonus items, which can directly raise your overall keyword ranking.

6. Summary and Selection List

Processing video transcoding in Tencent cloud ecosystem,

Computational (C-Series) is the undisputed general preferred

. Its high frequency, low memory redundancy features, natural fit CPU-intensive codec business.

Finally, give each webmaster and architect a final confirmation list:

If you want to maximize the calculation power of single-machine squeezing and pursue fast online $\rightarrow $, choose the calculation type C series.

The video volume is very large, the fault tolerance rate is high, and you want to save $\rightarrow $. Log in to the Tencent Cloud account to purchase a preemptible computing instance.

In addition to transcoding, this server should also take into account the huge Redis memory cache or streaming media distribution (mixed running is not recommended, but if the budget is really limited) $\rightarrow $choose the standard S series.